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The 2014 IACSIT Beijing Conferences
2014 IACSIT Beijing Conferences
2014 the 6th International Conference on Graphic and Image Processing
(ICGIP 2014)
2014 International conference on Networks and Information Security
(ICNIS 2014)
2014 International Conference on Robotics and Computer Vision
(ICRCV 2014)
Conference Schedule
Sponsored By
Beijing, China
October 24-26, 2014
www.icgip.org
www.icnis.org
www.icrcv.org
The 2014 IACSIT Beijing Conferences
Welcome to IACSIT Conference in
Beijing October 24-26, 2014
Dear Distinguished Delegates,
Welcome to the 2014 IACSIT Conference in Beijing, China. We’re confident that over the three days
you’ll get the theoretical grounding, practical knowledge, and personal contacts that will help you build
long-term, profitable and sustainable communication among researchers and practitioners working in
a wide variety of scientific areas with a common interest in Graphic and Image Processing; Networks
and Information Security and Robotics and Computer Vision.
After more than half a year’s preparation, we finally will have those conferences to be held in Beijing,
China during October 24-26, 2014
For the conferences of ICGIP 2014&ICNIS 2014&ICRCV 2014, we had received over 273 submissions,
89 excellent papers were accepted and published finally. Congratulations for those papers.
On behalf of IACSIT organization, I would like to thank all the authors as well as the Program
Committee members and reviewers. Their high competence, their enthusiasm, their time and expertise
knowledge, enabled us to prepare the high-quality final program and helped to make the conference
became a successful event.
Once again, thanks for coming to IACSIT conferences, we are delegate to higher and better
international conference experiences. We will sincerely listen to any suggestion and comment; we are
looking forward to meeting you next time.
Yours Sincerely,
Sophie Tsang
Director of Conference Department II, IACSIT
The 2014 IACSIT Beijing Conferences
ANNOUNCEMENT
*ICGIP 2014 conference papers will be published into the ICGIP proceedings, and will
be included in the SPIE Digital Library, and provided to the Web of Science
Conference Proceedings Citation Index-Science, Scopus, Ei Compendex, Inspec,
Google Scholar, Microsoft Academic Search, and others, to ensure maximum
awareness of the Proceedings.
ICNIS 2014 conference papers will be published in the following Journals with ISSN.

Journal of Advances in Computer Networks (JACN; ISSN: 1793-8244)
Abstracting/Indexing: Engineering & Technology Digital Library, EBSCO, DOAJ,
Electronic Journals Library, Ulrich's Periodicals Directory, International Computer
Science Digital Library (ICSDL), ProQuest, and Google Scholar.
ICRCV 2014 conference papers will be published in one of the following Journals with
ISSN.

International Journal of Computer Theory and Engineering (IJCTE; ISSN:
1793-8201)
Abstracting/Indexing: Index Copernicus, Electronic Journals Library, EBSCO,
Engineering & Technology Digital Library, Google Scholar, INSPEC, Ulrich's
Periodicals Directory, Crossref, ProQuest, WorldCat, and EI (INSPEC, IET).

Journal of Automation and Control Engineering(JOACE; ISSN: 2301-3702)
Abstracting/Indexing: Ulrich's Periodicals Directory, Google Scholar, EBSCO,
Engineering & Technology Digital Library and Electronic Journals Digital Library.
*One best presentation will be selected from each session, the best one will be
announced and award the certificate at the end of each session
IACSIT Publication committee
The 2014 IACSIT Beijing Conferences
Instructions for Oral Workshop
Devices Provided by the Conference Organizer:
 Laptops (with MS-Office & Adobe Reader)
 Projectors & Screen
 Laser Sticks
Materials Provided by the Presenters:
 PowerPoint or PDF files
Duration of each Presentation (Tentatively):
 Regular Oral Session: about 15 Minutes of Presentation 3 Minutes of Q&A
 Keynote Speech: 40 Minutes of Presentation including 5 Minutes of Q&A
The 2014 IACSIT Beijing Conferences
Conference Schedule
Day 1, Friday, October 24, 2014
Registration: The Lobby of JIANGXI GRAND HOTEL
10:00am-12:00pm
13:30pm-17:00pm
Arrival, Registration and Conference materials collection
**Certificate for Participation can be collected at the
registration counter**
Day 2, Saturday, October 25, 2014
09:00am-09:05am
Opening Remarks
Keynote Speech I:
09:05am-09:50am
Keynote Speech II:
Morning
09:50am-10:35am
Venue:
Multifuncti
onal Hall
(1st floor)
Prof. David Zhang
Hong
Kong
Polytechnic
University，Hong Kong
10:35am-10:55am
Prof. Xudong Jiang
Nanyang
Technological
University, China
Coffer Break
/
Plenary Photo
Keynote Speech III:
10:55am-11:40am
Prof. Ming Yang,
Southern
Polytechnic
University, USA
12:00pm-13:30pm Lunch
State
The 2014 IACSIT Beijing Conferences
Afternoon
13:00pm-15:30pm
Session I - Machine Vision
Venue:
15:30pm-16:00pm Coffee Break
Conference
room 2
15:30pm-18:00pm Session II - Image processing
(3rd floor)
Venue:
13:00pm-15:30pm
Session III - Pattern Recognition
Conference
15:30pm-16:00pm Coffee Break
room 3
(3rd floor)
15:30pm-18:00pm
Session IV-
Video processing and computer
vision
Venue:
13:00pm-15:30pm
Session V - 3D reconstruction and visualization
Conference 15:30pm-16:00pm Coffee Break
room 5
(3rd floor) 16:00pm-18:00pm Session V - 3D reconstruction and visualization
Dinner
18:00pm-20:30pm
Day 3, Sunday, October 26, 2014
One-day Tour
Set off in the hotel gate at 6:00 am
The 2014 IACSIT Beijing Conferences
Session I –Authors’ Oral Presentation
(ICNIS 2014 & ICRCV 2014)---Machine Vision
13:00am-15:30pm,
Session Chair: Dr. Weiping Zhu, University of New South Wales, Australia
Opening Presentation(IS001)
Network Topology Estimation using Normalized Temporal Correlation
Weiping Zhu
University of New South Wales, Australia
IS001
Abstract—Almost all of the previous works in topology discovery use an
indirect approach to estimate the topology of a network that introduce the
dependency between the feature extracted from observation and the topology to be
estimated. We in this paper advocate a direct approach to estimate the topology of
a network that uses temporal characteristic observed by receivers to overcome the
weakness of its predecessors. In addition, a number of features are proposed that
can be used to identify the topology. Simulation study is carried out that confirms
the direct approach can achieve the same as the indirect approach with less probes.
Index Terms—Correlation, Similarity, Time Series, Topology Inference
Trends & Future for Enterprise Integration
Usman bin Danish Chawla and Lareb Hussain Halepoto
Institute of Business Administration (IBA) – Karachi, Pakistan
IS005
Abstract—this is no surprise that the businesses today depend heavily on
information technology than they ever did. It is one of these technologies that have
made interoperability, interconnection and knitting of applications an easier task.
EAI is the combination of hardware and software to share data and process in
manner undisturbed and unrestricted for those applications and data files that have
been so integrated. This research report attempts to look at the evolution of EAI
and the challenges that it faces presently and in future.
Index Terms—Enterprise Integration, Trends, Service Bus
Optimal Fault-tolerant Multi-robot Team Design using Robot Reliability
GyuhoEoh, Beom H. Lee
Seoul National University, South Korea
CV004
Abstract—This paper presents an optimal multi-robot team design using robot
reliability for satisfying desired probability of mission completion in fault system.
The 2014 IACSIT Beijing Conferences
Previous studies in this area mainly described a quantitative analysis, but an
analytic solution for optimal multi-robot team organization was not presented. The
proposed method, however, suggests not only a quantitative analysis but also
provides necessary information for optimal team organization. In addition, an
algorithmic solution is also provided for the optimal multi-robot team design when
a faulty robot occurs. Simulated experiments are presented for verifying the
proposed method, which proves the efficiency of the method.
Index Terms—Reliability, multi-robot, fault-tolerant system reliability function
Enhanced Pose Estimation Method Using Selective Scan Data in Structured
Environments
Wonsok Yoo,Beom H. Lee
Seoul National University, South Korea
CV005
Abstract—This paper suggests enhanced robot pose estimation method by using
selective scan data in structured environments. Previous pose estimation
approaches, which estimate the pose by scan matching method, use scan data of
constant interval. However, these approaches do not consider the property that scan
matching result is affected by the scan data distribution in the overlapping areas
between two consecutive scans. Our proposed method varies scan interval in order
to adjust overlapping areas between current and next scans. Through the
experiments, we compared our method to the previous approaches which use
constant interval scans and verified improved performance of our new approach.
Index Terms—Robot, pose estimation, scan matching, map building, selective data
process
Kalman Consensus based Multi-robot SLAM with a Rao-Blackwellized Particle
Filter
Seung-Hwan Lee, Beom H. Lee
Seoul National University, South Korea
CV007
Abstract—This paper addresses a multi-robot SLAM approach based on the
Kalman consensus filter (KCF). Under the unknown initial condition, a reference
robot designates the initial poses of other robots when the first rendezvous between
them occurs. Accordingly, past and current poses and maps of these robots are
estimated by an acausal filter and a causal filter. If initialized robots meet again,
their current poses are updated using the KCF. Accordingly, their past poses and
maps until the most recent rendezvous are also compensated through the acausal
filter. In two simulations, the FastSLAM algorithm, which is a special case of
Rao-Blackwellized particle filters, was employed for SLAM. The performance of
the proposed approach was verified by comparing conventional approaches.
Index Terms—Kalman Consensus Filter, Rao-Blackwellized particle filter,
Multi-robot SLAM, FastSLAM
The 2014 IACSIT Beijing Conferences
Wheel Velocity Obstacles for Differential Drive Robot Navigation
Jae D. Jeon and Beom H. Lee
Seoul National University, South Korea
CV008
Abstract—In this paper, we deal with the real-time navigation problem of a
differential drive robot in dynamic environments. As a rule, the robot is controlled
by wheel velocity commands at sampling intervals and moves along a straight line
or a circular arc in accordance with those commands. Thus, we define the wheel
velocity obstacle, which is a set of all the left and right wheel velocity pairs that
induce collisions with obstacles within a given time horizon. Also, a navigation
strategy is suggested that will allow the robot to reach its destination without
colliding with obstacles. Our algorithm was found to outperform previously
released collision avoidance algorithms in terms of safety through Monte Carlo
simulations.
Index Terms—Collision avoidance, motion planning, velocity obstacles,
differential drive robot
Accurate Visual Loop-Closure Detection using Bag-of-Words for Multiple Robots
Jung H. Oh, Seung-Hwan Lee and Beom H. Lee
Seoul National University, South Korea
IV009
Abstract—We propose a method to detect loop-closures in a simultaneous
localization and mapping (SLAM) problem for multiple robots. Each robot should
be able to detect other robots’ previously visited locations from camera
measurements. To identify these places, our approach adapts the bag-of-words
method in image recognition, and improves it by applying a Gaussian filter and a
logistic function to correct the similarity scores. We can detect the robust
loop-closures using only visual information of multiple robots. Experiments are
performed to verify the effectiveness of the proposed method in indoor
environments.
Index Terms—Loop-closure, mobile robots, SLAM, visual feature, bag-of-word
Colored Point Cloud Registration with Improved Hue-Assisted Normal
Distributions Transform
Hyunki Hong and Beomhee Lee
Seoul National University, South Korea
Abstract—This paper describes an improved Hue-Assisted Normal Distributions
Transform (HANDT), which enhances the accuracy of the registration of point
clouds. In our previous work, HANDT was developed to improve the speed and
accuracy of registration by utilizing the hue from the hue-saturation-value model.
To improve the accuracy, the score function of HANDT is changed from the
normal distribution function to the Mahalanobis distance function. In addition, the
The 2014 IACSIT Beijing Conferences
CV015
functions of the hue mean and variance are modified for the circular property of the
hue. The performance of normal distributions transform (NDT), HANDT, and
improved HANDT are evaluated by benchmark data sets. As a result, the
translation and rotation errors of improved HANDT are lower than those of NDT
and HANDT.
Index Terms—Hue, color, point cloud, registration, normal distributions transform
(NDT)
Fast Image Diffusion for Feature Detection and Description
Lu Feng, Zhuangzhiwu and Xiang Long
BeiHang University, China
CV017
Abstract—In this paper, we introduce a new multiscale 2D feature detection and
description method based on optimal O(1) bilateral filter feature (OBFF). Existing
methods detect and describe features by analyzing the scale space generated by
linear and nonlinear diffusion kernel function, like Gaussian scale space and
anisotropic diffusion scale space. By using the anisotropic diffusion scale space,
KAZE features achieve significant progress on the 2D feature detection by using
the anisotropic diffusion scale space. It makes the blurring locally adaptive and
retains better feature localization accuracy and distinctiveness than the SIFT
method. Our method OBFF also generates the nonlinear scale space of image to
detect the local feature. The optimal bilateral filter is advantage in object boundary
preserving and antinoise ability and dramatically speed up feature detection in
nonlinear scale space. We use the benchmark datasets to compare our method with
state-of-the-art approaches.
Index Terms—Bilateral filter, Nonlinear scale space, Feature detection, SIFT,
Binary descriptor
A Leukocyte Detection System using Scale Invariant Feature Transform Method
Lina Lina, Arlends Chris, Bagus Mulyawan, and Agus Budi Dharmawan
Tarumanagara University, Indonesia
CV018
Abstract—Image inpainting is an important research topic in the field of image
processing. The objective of inpainting is to “guess” the lost information according
to surrounding image information, which can be applied in old photo restoration,
object removal and demosaicing. Based on the foundation of previous literature of
image inpainting and image modeling, this paper provides an overview of the
state-of-art image inpainting methods. This survey first covers mathematics models
of inpainting and different kinds of image impairment. Then it goes to the main
components of an image, the structure and the texture, and states how these
inpainting models and algorithms deal with the two separately, using PDE’s
method, exemplar-based method and etc. Afterwards sparse-representation-based
inpainting and related techniques are introduced. Experimental analysis will be
presented to evaluate the relative merits of different algorithms, with the measure
The 2014 IACSIT Beijing Conferences
of Peak Signal to Noise Ratio (PSNR) as well as direct visual perception.
Index Terms—Image inpainting, variational method, partial differential
equation(PDE), exemplar based method, sparse representation
A novel 3D camera based supervision system for safe human-robot interaction in
the operating room
Philip Nicolai, Jörg Raczkowsky, Heinz Wörn
Karlsruhe Institute of Technology, Germany
CV020
Abstract—In anticipation of upcoming technological advances in the operating
room, it is necessary to already give thought to how humans and robots can safely
interact and cooperate in the operating room of the future. In this paper, we present
a supervision system, consisting of seven 3D cameras, and the according shape
cropping algorithm, which allows verifying the correct setup of surgical robots,
detecting potential collisions between robots and their surroundings as well as
monitoring the correctness of the robots’ motions. The system has already been
successfully implemented, set up and evaluated.
Index Terms—Robot assisted surgery, surgical robots, human-machine interaction,
scene supervision
Session II –Authors’ Oral Presentation
(ICGIP 2014)--- Image processing
15:30pm-18:00pm,
Session Chair: Dr. Hui Yu, University of Portsmouth, the United Kingdom
A Multi-scale Fusion-based Dark Channel Prior Dehazing Algorithm
Yujun Zeng, Xiaolin Liu
College of Mechatronic Engineering and Automation, National University of
Defense Technology, Changsha, China
IP001
Abstract—During model-based image dehazing, the role of the accuracy of
transmission estimation is crucial, which has a decisive effect on the final result.
Considering that an ideal transmission map must be smooth, edge-preserving and
free of redundant false details, a fusion-based dark channel prior (DCP) dehazing
algorithm is presented in this paper. On the basis of DCP, a pixel-wise and a
patch-wise transmission maps are obtained. Then an L0 smoothing filter and a
large scale Gaussian filter are applied to them respectively. Finally, a much more
accurate refined transmission map is attained through fusion and a haze-free
image is restored using the atmosphere degradation model. Furthermore, a novel
scheme for setting the lower bound of transmission adaptively is also put
The 2014 IACSIT Beijing Conferences
forward. Experiments demonstrate a better and faster dehazing capability over
original DCP algorithm and state-of-the-art dehazing methods, especially in
suppressing halo artifacts, restoring details and coping with the haze existing in
small-scale areas of depth discontinuity occluded by foreground..
Index Terms—Dehaze, dark channel prior, L0 smoothing, fusion
Sparse Principle Component Analysis for Single Image Super-Resolution
Qianying Zhang, Jitao Wu
School of Mathematics and Systems Science, Beihang University, China
IP007
Abstract—In this paper, we propose a novel image super-resolution method
based on sparse principle component analysis. Various coupled sub-dictionaries
are trained to represent high-resolution and low-resolution image patches. The
proposed method simultaneously exploits the incoherence of the sub-dictionaries
and nonlocal self-similarity existing in natural images. The purpose of
introducing these two regularization terms is to design a novel dictionary learning
algorithm for having good reconstruction. Furthermore, in the dictionary learning
process, the algorithm can update the dictionary as a whole and reduce the
computational cost significantly. Experimental results show the efficiency of the
proposed method compared to the existing algorithms in terms of both PSNR and
visual perception.
Index Terms—Super-resolution, sub-dictionary learning, sparse representation,
sparse principle component analysis
Anaglyph videoanimations from oblique stereoimages
Vit Vozenilek, Tomas Kralik
Palacky University Olomouc, Czech Republic
IP014
Abstract—The paper deals with the approach of compiling of animations from
a pair of oblique stereoimages. The authors investigated as simple and cheap way
as possible to develop such approach which will be available for wide scope of
ordinary users with common equipment. They concentrated on three procedures
of oblique stereoimage handling to compile sets of images, animations and
analogue documents. After capturing construction site by a pair of web cameras
the data were corrected, photogrammetrically adjusted (due to radial distortion)
and exported. Firstly, a set of anaglyphic images were compiled, then they were
trimmed and timeline was inserted. The final anaglyph animations are compiled
in various versions. In addition, an anaglyphic book containing 150 images was
created in a special way that the user can easily browse through its content. The
main outputs are several unique anaglyph products, but more beneficial outputs
are developed procedures of anaglyph visualization that can be applied with
minor modifications to photographing of any objects.
Index Terms—anaglyph image, videoanimation, geovisualization
A Comparison of Image Inpainting Techniques
Liu Yaojie, Shu Chang
The 2014 IACSIT Beijing Conferences
School of Communication and Information Engineering, University of Electronic
Science and Technology of China, China
IP018
Abstract—Image inpainting is an important research topic in the field of image
processing. The objective of inpainting is to “guess” the lost information
according to surrounding image information, which can be applied in old photo
restoration, object removal and demosaicing. Based on the foundation of previous
literature of image inpainting and image modeling, this paper provides an
overview of the state-of-art image inpainting methods. This survey first covers
mathematics models of inpainting and different kinds of image impairment. Then
it goes to the main components of an image, the structure and the texture, and
states how these inpainting models and algorithms deal with the two separately,
using PDE’s method, exemplar-based method and etc. Afterwards
sparse-representation-based inpainting and related techniques are introduced.
Experimental analysis will be presented to evaluate the relative merits of
different algorithms, with the measure of Peak Signal to Noise Ratio (PSNR) as
well as direct visual perception.
Index Terms—Image inpainting, variational method, partial differential
equation(PDE), exemplar based method, sparse representation
A Novel Color Filter Array and Demosaicking Algorithm for Hexagonal Grids
Alexander Fröhlich and Andreas Unterweger
Salzburg University of Applied Sciences, Austria
IP023
Abstract—We propose a new color filter array for hexagonal sampling grids
and a corresponding demosaicking algorithm. By exploiting properties of the
human visual system in their design, we show that our proposed color filter array
and its demosaicking algorithm are able to outperform the widely used Bayer
pattern with state-of-the-art demosaicking algorithms in terms of both, objective
and subjective image quality.
Index Terms—Hexagonal Sampling, Color Filter Array, Demosaicking
Effective and Fully Automatic Image Segmentation Using Quantum Entropy and
Pulse-Coupled Neural Networks
Songlin Du, Yaping Yan, and Yide Ma
School of Information Science and Engineering, Lanzhou University, China
IP040
Abstract—A novel image segmentation algorithm which uses quantum entropy
and pulse-coupled neural networks (PCNN) is proposed in this paper. Optimal
iteration of the PCNN is one of the key factors affecting segmentation accuracy.
We borrow quantum entropy from quantum information to act as a criterion in
determining optimal iteration of the PCNN. Optimal iteration is captured while
total quantum entropy of the segments reaches a maximum. Moreover, compared
with other PCNN-employed algorithms, the proposed algorithm works without
any manual intervention, because all parameters of the PCNN are set
The 2014 IACSIT Beijing Conferences
automatically. Experimental results prove that the proposed method can achieve
much lower probabilities of error segmentation than other PCNN-based image
segmentation algorithms, and this suggests that higher image segmentation
quality is achieved by the proposed method.
Index Terms—Image segmentation, pulse-coupled neural networks, quantum
entropy, fully automatic
An image denoising algorithm based on clustering and median filtering
Wang YuLing , Li Ming, Li Li
Department of Automation Engineering, Nanjing University of Aeronautics and
Astronautics, China
IP059
Abstract—It is proposed of an improved median de-noising method, namely
an image de-noising algorithm based on clustering and median filtering. The
algorithm is a kind of image fast de-noising method based on the clustering idea,
the singular point points are isolated from the image and then clustering. It is
advantage to better protect the details of an image and to substantially reduce
calculation. Compared with traditional median filter, mean filter and wiener filter,
our approach is more adaptive and receives better results. While for images that
have complex details such as texture images, the results of experiment show that
the proposed algorithm works less well in the de-noising effect comparatively.
Index Terms—image de-noising, clustering algorithm, median filter, PSN
A Self-Adaptive Anti-Vibration Pipeline-Filtering Algorithm
Houde Wu, Bin Wang, Ming Zhao , Wenhai Xu
College of Information Science Technology, Dalian Maritime University, China
IP070
IP080
Abstract—The mobile pipeline-filtering algorithm is a real-time algorithm that
performs well in detecting small dim targets, but it is particularly sensitive to
interframe vibration of sequence images. When searching for small dim targets at
sea based on an infrared imaging system, irregular and random vibration of the
airborne imaging platform causes huge interference problems for the mobile
pipeline-filtering. This paper puts forward a pipeline-filtering algorithm that has a
good performance on self-adaptive anti-vibration. In the block matching method
using the normalized cross-correlations coefficient (NCC), the interframe
vibration of sequence images is acquired in real time and used to correct
coordinates of the single-frame detection results, and then the corrected detection
results are used to complete the mobile pipeline-filtering. Experimental results
show that the algorithm can overcome the problem of interframe vibration of
sequence images, thus realizing accurate detection of small dim maritime targets.
Index Terms—pipeline-filtering, anti-vibration, small dim target detection,
infrared sequence images
Image Haze Removal Algorithm for transmission lines Based on weighted
Gaussian PDF
WANG Wanguo , ZHANG Jingjing, LI Li, WANG Zhenli, LI Jianxiang, ZHAO
The 2014 IACSIT Beijing Conferences
Jinlong
Electric Power Robotics Laboratory of SGCC, Shandong Electric Power
Research Institute , China
Abstract—Histogram specification is a useful algorithm of image enhancement
field. This paper proposes an image haze removal algorithm of histogram
specification based on the weighted Gaussian probability density function
(Gaussian PDF). Firstly, we consider the characteristics of image histogram that
captured when sunny, fogging and haze weather. Then, we solve the weak
intensity of image specification through changing the variance and weighted
Gaussian PDF. The performance of the algorithm could removal the effective of
fog and experimental results show the superiority of the proposed algorithm
compared with histogram specification. It also has much advantage in respect of
low computational complexity, high efficiency, no manual intervention.
Index Terms—Gaussian PDF, Histogram specification, image haze removal
Sparse representation using multiple dictionaries for single image super-resolution
Yih-Lon Lin, Chung-Ming Sung, and Yu-Min Chiang
Department of Information Engineering, I-Shou University, Taiwan
IP091
Abstract—New algorithms are proposed in this paper for single image
super-resolution using multiple dictionaries based on sparse representation. In the
proposed algorithms, a classifier is constructed which is based on the edge properties
of image patches via the two lowest discrete cosine transformation (DCT)
coefficients. The classifier partitions all training patches into three classes. Training
patches from each of the three classes can then be used for the training of the
corresponding dictionary via the K-SVD (singular value decomposition) algorithm.
Experimental results show that the high resolution image quality using the proposed
algorithms is better than that using the traditional bi-cubic interpolation and Yang’s
method.
Index Terms—Image super-resolution, sparse representation, image patch
classification
Weakly Supervised Glasses Removal
Zhicheng Wang and Yisu Zhou
School of Software, Tsinghua University, China
IP095
Abstract—Glasses removal is an important task on face recognition, in this paper,
we provide a weakly supervised method to remove eyeglasses from an input face
image automatically. We choose sparse coding as face reconstruction method, and
optical flow to find exact shape of glasses. We combine the two processes iteratively
to remove glasses more accurately. The experimental results reveal that our method
works much better than these algorithms alone, and it can remove various glasses to
obtain natural looking glassless facial images.
The 2014 IACSIT Beijing Conferences
Index Terms—Glasses removal, Sparse coding, Optical flow, Face reconstruction
Pupil Segmentation Using Active Contour with Shape Prior
Charles Ukpai, Satnam. S. Dlay and Wai. L. Woo
University of Newcastle Upon-Tyne, United Kingdom
IP110
Abstract—Segmentation is the process of defining the valid part/s of an image whi
ch will be used for further processing like feature extraction, matching and decision
making. Several segmentation algorithms have been developed for iris images howev
er, they are mostly based on the assumption that iris boundaries has a circular shape.
Here, we are interested in pupil segmentation which is a very important step in iris re
cognition. In most pupil segmentation algorithms, it is often assumed that the pupil is
circular in shape and few that considered non-circularity of the pupil paid little attenti
on to time. These methods lead to inaccurate pupil segmentation for pupils with noncircular boundaries or a system which is too slow for real life implementation. In this
paper, we propose a new pupil segmentation method based on active contour model
with shape prior. Initially, the pupil’s position and radius is estimated using a statistic
al procedure and circular Hough transform. Finally, the active contour model is initia
lized close to the pupil’s boundary using information from the first step and segmenta
tion is achieved using energy minimization based active contour. Pre-processing and
post-processing were carried out to remove noise and reflections and remove occlusi
ons respectively. Experimental results on CASIA V1.0 and 4.0 shows that the propos
ed method is highly effective at segmenting irregular boundaries of the pupil.
IndexTerms—pupil segmentation, active contour, feature extraction, biometrics, iris
segmentation
Session III–Authors’ Oral Presentation
(ICGIP 2014)---Pattern Recognition
13:00pm-15:30pm,
Session Chair: Prof. Vit Vozenilek, Palacky University, Czech Republic
A Review of recent advances in 3D Face Recognition
Jing Luo, Shu Ze Geng, Zhao Xia Xiao,Chun Bo Xiu
Tianjin Polytechnic University, China.
IP003
Abstract—Face recognition based on machine vision has achieved great advances
and been widely used in the various fields. However, there are some challenges on
the face recognition, such as facial pose, variations in illumination, and facial
The 2014 IACSIT Beijing Conferences
expression. So, this paper gives the recent advances in 3D face recognition. 3D face
recognition approaches are categorized into four groups: minutiae approach, space
transform approach, geometric features approach, model approach. Several typical
approaches are compared in detail, including feature extraction, recognition
algorithm, and the performance of the algorithm. Finally, this paper summarized the
challenge existing in 3D face recognition and the future trend. This paper aims to
help the researches majoring on face recognition.
Index Terms—3D face recognition, geometric features, space transform, minutiae
approach
Combining Appearance and Geometric Features for Facial Expression Recognition
Hui Yu, Honghai Liu
University of Portsmouth, Portsmouth, UK
IP202
Abstract—This paper introduces a method for facial expression recognition
combining appearance and geometric facial features. The proposed framework
consistently combines multiple facial representations at both global and local levels.
First, covariance descriptors are computed to represent regional features combining
various feature information with a low dimensionality. Then geometric features are
detected to provide a general facial movement description of the facial expression.
These appearance and geometric features are combined to form a vector
representation of the facial expression. The proposed method is tested on the CK+
database and shows encouraging performance.
Index Terms—Geometric features, covariance descriptors, facial expression, facial
patches
Adaptive Object Tracking via both positive and negative models Matching
Shaomei Li, Chao Gao,Yawen Wang
Information Technology Research Center of PLA Information Engineering
University, China
IP039
IP044
Abstract—To improve tracking drift which often occurs in adaptive tracking, an
algorithm based on the fusion of tracking and detection is proposed in this paper.
Firstly, object tracking is posed as abinary classification problem and is modeled by
partial least squares (PLS) analysis. Secondly, tracking object frame by frame via
particle filtering. Thirdly, validating the tracking reliability based on both positive
and negative models matching. Finally, relocating the object based on SIFT features
matching and voting when drift occurs. Object appearance model is updated at the
same time. The algorithm can not only sense tracking drift but also relocate the
object whenever needed. Experimental results demonstrate that this algorithm
outperforms state-of-the-art algorithms on many challenging sequences.
Index Terms—object tracking; tracking drift; partial least squares analysis; positive
and negative models matching
A Novel Hybrid Motion Detection Algorithm Based On 2-D Histogram
Xiaomeng Su, Haiying Wang
China Mobile Group Design Institute Co., Ltd., China
The 2014 IACSIT Beijing Conferences
Abstract—This article proposes a novel hybrid motion detection algorithm based
on 2-D (2-Dimensional) spatio-temporal states histogram. The new algorithm
combines the idea of image change detection based on 2-D histogram and
spatio-temporal entropy image segmentation. It quantifies the continuity of pixel
state in time and space domain which are called TDF (Time Domain Filter) and SDF
(Space Domain Filter) respectively. After this, put both channels of output data from
TDF and SDF into a 2-D histogram. In the 2-D histogram, a curve division method
helps to separate the foreground state points and the background ones more
accurately. Innovatively, the new algorithm converts the video sequence to its
histogram sequence, and transforms the difference of pixel’s value in the video
sequence into the difference of pixel’s position in the 2-D histogram. Experimental
results on different types of scenes added Gaussian noise shows that the proposed
technique has strong ability of detecting moving objects.
Index Terms—Motion detection, noise reducing, 2-D histogram, spatio-temporal
property, contrast enhancement
Two Dimensional Discriminant Neighborhood Preserving Embedding In Face
Recognition
Meng Pang, Jifeng Jiang, Chuang Lin and Binghui Wang
School of Software, Dalian University of Technology, China
IP057
Abstract—One of the key issues of face recognition is to extract the features of
face images. In this paper, we propose a novel method, named two-dimensional
discriminant neighborhood preserving embedding (2DDNPE), for image feature
extraction and face recognition. 2DDNPE benefits from four techniques, i.e.,
neighborhood preserving embedding (NPE), locality preserving projection (LPP),
image based projection and Fisher criterion. Firstly, NPE and LPP are two popular
manifold learning techniques which can optimally preserve the local geometry
structures of the original samples from different angles. Secondly, image based
projection enables us to directly extract the optimal projection vectors from
two-dimensional image matrices rather than vectors, which avoids the small sample
size problem as well as reserves useful structural information embedded in the
original images. Finally, the Fisher criterion applied in 2DDNPE can boost face
recognition rates by minimizing the within-class distance, while maximizing the
between-class distance. To evaluate the performance of 2DDNPE, several
experiments are conducted on the ORL and Yale face datasets. The results
corroborate that 2DDNPE outperforms the existing 1D feature extraction methods,
such as NPE, LPP, LDA and PCA across all experiments with respect to recognition
rate and training time. 2DDNPE also delivers consistently promising results
compared with other competing 2D methods such as 2DNPP, 2DLPP, 2DLDA and
2DPCA.
Index Terms—Two-dimensional projection, Fisher criterion, Feature extraction,
Neighborhood preserving embedding (NPE), Locality preserving projection (LPP)
The 2014 IACSIT Beijing Conferences
Missile placement analysis based on improved SURF feature matching algorithm
Kaida Yang, Wenjie Zhao, Dejun Li, Xiran Gong, Qian Sheng
Aviation University of Air Force, China
IP061
Abstract—The precious battle damage assessment by use of video images to
analysis missile placement is a new study area. The article proposed an improved
speeded up robust features algorithm named restricted speeded up robust features,
which combined the combat application of TV-command-guided missiles and the
characteristics of video image. Its restrictions mainly reflected in two aspects, one is
to restrict extraction area of feature point; the second is to restrict the number of
feature points. The process of missile placement analysis based on video image was
designed and a video splicing process and random sample consensus purification
were achieved. The RSURF algorithm is proved that has good real-time performance
on the basis of guarantee the accuracy.
Index Terms—missile placement analysis, speeded-up robust features, restricted
speeded-up robust features, TV-command-guided missile, target damage assessment
Detection and Recognition of Uneaten Fish Food Pellets in Aquaculture using Image
Processing
Huanyu Liu, Lihong Xu , Dawei Li
College of Electronics and Information Engineering, Tongji University, China
IP071
Abstract—The waste of fish food has always been a serious problem in
aquaculture. On one hand, the leftover fish food spawns a big waste in the
aquaculture industry because fish food accounts for a large proportion of the
investment. On the other hand, the left over fish food may pollute the water and
make fishes sick. In general, the reason for fish food waste is that there is no
feedback about the consumption of delivered fish food after feeding. So it is
extremely difficult for fish farmers to determine the amount of feedstuff that should
be delivered each time and the feeding intervals. In this paper, we propose an
effective method using image processing techniques to solve this problem. During
feeding events, we use an underwater camera with supplementary LED lights to
obtain images of uneaten fish food pellets on the tank bottom. An algorithm is then
developed to figure out the number of left pellets using adaptive Otsu thresholding
and a linear-time component labeling algorithm. This proposed algorithm proves to
be effective in handling the non-uniform lighting and very accurate number of
pellets are counted in experiments.
Index Terms—Fish food pellets recognition, image processing, Otsu algorithm,
connected area algorithm.
Supervised Descent Method with Low rank and Sparsity Constraints for Robust
Face Alignment
Yubao Sun, Jiankang deng
Nanjing University of Information Science and Technology, China
The 2014 IACSIT Beijing Conferences
IP086
Abstract—Supervised Descent Method (SDM) learns the descent directions of
nonlinear least square objective in a supervised manner, which has been efficiently
used for face alignment. However, SDM still may fail in the cases of partial
occlusions and serious pose variations. To deal with this issue, we present a new
method for robust face alignment by utilizing the low rank prior of human face and
enforcing sparse structure of the descent directions. Our approach consists of low
rank face frontalization and sparse descent steps. Firstly, in terms of the low rank
prior of face image, we recover such a low-rank face from its deformed image and
the associated deformation despite significant distortion and corruption. Alignment
of the recovered frontal face image is more simple and effective. Then, we propose a
sparsity regularized supervised descent model by enforcing the sparse structure of
the descent directions under the l1constraint, which makes the model more effective
in computation and robust to partial occlusion. Extensive results on several
benchmarks demonstrate that the proposed method is robust to facial occlusions and
pose variations.
Index Terms—Face alignment; sparse descent direction; low rank texture.
A Statistical Description of 3D Lung Texture from CT Data
Kraisorn Chaisaowong, Andreas Paul
King Mongkut's University of Technology North Bangkok, Thailand
IP087
Abstract—A method was described to create a statistical description of 3D lung
texture from CT data. The second order statistics, i.e. the gray level co-occurrence
matrix (GLCM), has been applied to characterize texture of lung by defining the
joint probability distribution of pixel pairs. The required GLCM was extended to
three-dimensional image regions to deal with CT volume data. For a fine-scale lung
segmentation, both the 3D GLCM of lung and thorax without lung are required.
Once the co-occurrence densities are measured, the 3D models of the joint
probability density function for each describing direction of involving voxel pairs
and for each class (lung or thorax) are estimated using mixture of Gaussians through
the expectation-maximization algorithm. This leads to a feature space that describes
the 3D lung texture.
Index Terms—CT, lung, segmentation, pattern recognition, texture extraction,
statistical models, co-occurrence matrix
Saliency Region and Density Maximization for Salient Object Detection
Xin He, Huiyun Jing
National Computer Network Emergency Response Technical Team / Coordination
Center of China, China
IP090
Abstract—In this paper, we propose an alternative salient object detection method
based on maximum saliency region and density. The proposed approach can
automatically detect the salient object with a well-defined boundary. Saliency region
and density maximization is used as the quality function to find the optimal window
containing a salient object. And for efficiently executing window search, a
The 2014 IACSIT Beijing Conferences
branch-and-bound search algorithm based on saliency region and density is
proposed. Then the located window is used to initialize the GrabCut method, and the
salient object with a well- defined boundary is extracted through applying GrabCut.
Experimental results show that the proposed salient object detection approach
outperforms the state-of-the-art methods.
Index Terms—Salient object detection, Branch-and bound search, Saliency region
and density maximization
Multi-lane detection based on multiple vanishing points detection
Chuanxiang Li, Yiming Nie, Bin Dai, Tao Wu
College of Mechatronic Engineering and Automation, National University of
Defense Technology, Changsha, China
IP107
Abstract—Lane detection plays a significant role in Advanced Driver Assistance
Systems (ADAS) for intelligent vehicles. In this paper we present a multi-lane
detection method based on multiple vanishing points detection. A new multi-lane
model assumes that a single lane, which has two approximately parallel boundaries,
may not parallel to others on road plane. Non-parallel lanes associate with different
vanishing points. A biological plausibility model is used to detect multiple vanishing
points and fit lane model. Experimental results show that the proposed method can
detect both parallel lanes and non-parallel lanes.
Index
Terms—Multi-lane
detection,
winner-take-all, inhibition of return
multi-vanishing
point
detection,
Gaze Estimation using a Hybrid Appearance and Motion Descriptor
Chunshui Xiong, Lei Huang, Changping Liu
Institute of Automation, Chinese Academy of Sciences, China
IP022
Abstract—It is a challenging problem to realize a robust and low cost gaze
estimation system. Existing appearance-based and feature-based methods both have
achieved impressive progress in the past several years, while their improvements are
still limited by feature representation. Therefore, in this paper, we propose a novel
descriptor combining eye appearance and pupil center-cornea reflections (PCCR).
The hybrid gaze descriptor represents eye structure from both feature level and
topology level. At the feature level, a glints-centered appearance descriptor is
presented to capture intensity and contour information of eye, and a polynomial
representation of normalized PCCR vector is employed to capture motion
information of eyeball. At the topology level, the partial least squares is applied for
feature fusion and selection. At last, sparse representation based regression is
employed to map the descriptor to the point-of-gaze (PoG). Experimental results
show that the proposed method achieves high accuracy and has a good tolerance to
head movements.
Index Terms—Gaze estimation, hybrid appearance and motion descriptor, pupil
center-cornea reflections, partial least squares, sparse representation
The 2014 IACSIT Beijing Conferences
Session IV–Authors’ Oral Presentation
(ICGIP 2014)--- Video processing and computer vision
15:30pm-18:00pm,
Session Chair: Asst.Prof. Jing Luo, Tianjin Polytechnic University, China
Groupwise Surface Correspondence Using Particle Filtering
Guangxu Li, Hyoungseop Kim, Joo Kooi Tan and Seiji Ishikawa
School of Electronics and Information Engineering, Tianjin Polytechnic University,
China
IP011
Abstract—To obtain an effective interpretation of organic shape using statistical
shape models (SSMs), the correspondence of the landmarks through all the training
samples is the most challenging part in model building. In this study, a
coarse-to-fine groupwise correspondence method for 3-D polygonal surfaces is
proposed. We manipulate a reference model in advance. Then all the training
samples are mapped to a unified spherical parameter space. According to the
positions of landmarks of the reference model, the candidate regions for
correspondence are chosen. Finally we refine the perceptually correct
correspondences between landmarks using particle filter algorithm, where the
likelihood of local surface features are introduced as the criterion. The proposed
method was performed on the correspondence of 9 cases of left lung training
samples. Experimental results show the proposed method is flexible and
under-constrained.
Index Terms—Statistical shape model, correspondence, particle filter
Image Authentication via Sparsity-Based Phase-Shifting Digital Holography
Wen Chen and Xudong Chen
Department of Electrical and Computer Engineering, National University of
Singapore, Singapore
IP012
Abstract—Digital holography has been widely studied in recent years, and a
number of applications have been demonstrated. In this paper, we demonstrate that
sparsity-based phase-shifting digital holography can be applied for image
authentication. In phase-shifting digital holography, the holograms are sequentially
recorded. Only small parts of each hologram are available for numerical
reconstruction. It is found that nonlinear correlation algorithm can be applied to
simply authenticate the reconstructed object. The results illustrate that the recovered
image can be correctly verified. In the developed system, the recorded holograms are
highly compressed which can facilitate data storage or transmission, and one simple
authentication strategy has been established instead of applying relatively complex
algorithms (such as compressive sensing) to recover the object.
The 2014 IACSIT Beijing Conferences
Index Terms—Image authentication, holography-based security, sparsity constraint.
Fast Ellipse Detection by Elliptical Arcs Extracting and Grouping
Yipeng Li, Chunhui Zhao
Beijing Institute of Control Engineering, China
IP030
Abstract—A novel and simple ellipse detection method is proposed in this paper.
First, Canny operator is carried on the gray image to get edge image. Second, all the
edge segments are obtained from edge image and output gradients of edge segments
for further analysis. According to gradient direction, the edge segments are split into
primitive lines and arcs. Then elliptical arcs are extracted from the results of
splitting and an efficient grouping strategy is proposed to group elliptical arcs
coming from the same ellipse as candidate ellipse. Finally, least-square fitting
method is implemented to estimate the parameters of these candidate ellipses.
Experiment results show that the proposed method is robust to noise and fast for
real-time implementation.
Index Terms—Ellipse detection; arc segments; gradient direction; least-square
fitting method
Target Confirmation and Relocation using the Correlation Filter in Mean Shift
Tracking
Yi Song, Shuxiao Li, Hongxing Chang
Institute of Automation, Chinese Academy of Sciences, China
IP031
IP054
Abstract—The accurate locating for the target is critical for robust visual tracking
methods. This paper addresses the target position confirmation and relocation in
mean shift tracking, and proposes a novel method to integrate a MOSSE based
correlation filter into the mean shift tracker to obtain its ability of accurate locating.
To confirm whether the estimated location of the target is accurate, four measures
are evaluated. If the proposed conditions for relocating the target are satisfied, the
estimated target position will be adjusted to be more accurate. When the target is
occluded, a relocating approach is developed using the correlation filter to find the
target after occlusion. The target model and the filter template are updated in each
frame according to the evaluation results of the estimated target. Experimental
results show the integration of the correlation filter can help the mean shift tracker
locate and relocate the target well.
Index Terms—object tracking, mean shift, target relocation, correlation filter
Heuristic-driven GraphWavelet Modeling of Complex Terrain
Teodor Cioaca, Bogdan Dumitrescu, Mihai-Sorin Stupariu, Ileana P˘atru-Stupariu,
Magdalena N˘ap˘arus¸, Ioana Stoicescu, Alexander Peringer, Alexandre Buttler and
Franc¸ois Golay
University Politehnica of Bucharest, Romania
The 2014 IACSIT Beijing Conferences
Abstract—We present a novel method for building a multiresolution
representation of large digital surface models. The surface points coincide with the
nodes of a planar graph which can be processed using a critically sampled, invertible
lifting scheme. To drive the lazy wavelet node partitioning, we employ an attribute
aware cost function based on the generalized quadric error metric. The resulting
algorithm can be applied to multivariate data by storing additional attributes at the
graph’s nodes. We discuss how the cost computation mechanism can be coupled
with the lifting scheme and examine the results by evaluating the root mean square
error. The algorithm is experimentally tested using two multivariate LiDAR sets
representing terrain surface and vegetation structure with different sampling
densities.
Index Terms—Graph wavelets, terrain modeling, multivariate heuristic cost
Modeling synthetic radar image from a digital terrain model
Philippe Durand, Luan Jaupi, Dariush Ghorbanzadeh and Jean Paul Rudant
Conservatoire national des arts et metiers, France
IP004
Abstract—In this paper we propose to simulate SAR radar images that can be
acquired by aircraft or satellite. This corresponds to a real problematic, in fact, an
airborne radar data acquisition campaign, was conducted in the south east of France.
We want to estimate the geometric deformations that a digital terrain model can be
subjected. By extrapolation, this construction should also allow to understand the
image distortion if a plane is replaced by a satellite. This manipulation allow to
judge the relevance of a space mission to quantify geological and geomorphological
data, the radar wave is an electromagnetic wave, they have the advantage of
overcoming atmospheric conditions since more wavelength is large is better crossing
the cloud layer. Therefore imaging radar provides continuous monitoring
Index Terms—Radar SAR images, mnt
Video Object Segmentation via Adaptive Threshold based on Background Model
Diversity
Boubekeur Mohamed Bachir, SenLin Luo, Labidi Hocine and Benlefki Tarek
School of Information and Electronics, Beijing Institute of Technology, China
IP081
Abstract—The background subtraction could be presented as classification
process when investigating the upcoming frames in a video stream, taking in
consideration in some cases: a temporal information, in other cases the spatial
consistency, and these past years both of the considerations above. The classification
often relied in most of the cases on a fixed threshold value. In this paper, a
framework for background subtraction and moving object detection based on
adaptive threshold measure and short/long frame differencing procedure is proposed.
The presented framework explored the case of adaptive threshold using mean
squared differences for a sampled background model. In addition, an intuitive update
policy which is neither conservative nor blind is presented. The algorithm succeeded
on extracting the moving foreground and isolating an accurate background.
The 2014 IACSIT Beijing Conferences
Index Terms—Background Subtraction, video object segmentation, surveillance,
square successive differences
An Experimental Evaluation of Some Background Subtraction Algorithms Under a
Variety of Video Surveillance Challenges
Benlefki Tarek, Rongke Liu, Boubekeur Mohamed Bachir, Labidi Hocine
School of Electronics and Information Engineering, China
IP082
Abstract—This paper analyses the behavior of some existing background
subtraction algorithms for possible use in automated video surveillance applications.
The performance of the analyzed algorithms has been demonstrated by their authors
on a selected video sequences to show the merits of their approaches. Nevertheless,
choosing an adequate approach for a given application is not an easy task. In this
study; by using background subtraction evaluation metrics combined with visual
inspection, we asses in deep the performance of 04 algorithms under a variety of
video surveillance challenges. This experimental analysis highlights the advantages
and the limitations of each approach and helps in choosing the suitable method for a
given video surveillance scenario.
Index Terms—Video surveillance challenges, background subtraction algorithms,
moving object detection.
A robust Mean-shift Tracking Through Occlusion and Scale Based on Object
Trajectory for Surveillance Camera
Hocine Labidi, Sen-Lin Luo, Boubekeur Mohamed Bachir
Department of Information and Electronic, Beijing Institute of Technology, China
IP084
IP085
Abstract—Object tracking is an important part in surveillance systems, One of the
algorithms used for this task is the mean-shift algorithm due to the robustness,
computational efficiency and implementation ease. However the traditional
mean-shift cannot effectively track the moving object when the scale changes,
because of the fixed size of the tracking window, and can lose the target while an
occlusion, In this study a method based on the trajectory direction of the moving
object is presented to deal with the problem of scale change. Furthermore a
histogram similarity metric is used to detect when target occlusion occurs, and a
method based on multi kernel is proposed, to estimate which part is not in occlusion
and this part will be used to extrapolate the motion of the object and gives an
estimation of its position, Experimental results show that the improved methods
have a good adaptability to the scale and occlusion of the target.
Index Terms—Object tracking, Mean-shift, histogram similarity. target occlusion,
scale changing.
Real-time Video Analysis for Retail Stores
Ehtesham Hassan and Avinash Kumar Maurya
Department of Information and Electronic, Beijing Institute of Technology, China
The 2014 IACSIT Beijing Conferences
Abstract—With the advancement in video processing technologies, we can
capture subtle human responses in an retail store environment which play decisive
role in the store management. In this paper, we present a novel surveillance video
based analytic system for retail stores targeting localized and global traffic estimate.
Development of an intelligent system for human traffic estimation in real-life poses
a challenging problem because of the variation and noise involved. In this direction,
we begin with a novel human tracking system by an intelligent combination of
motion based and image level object detection. We demonstrate the initial evaluation
of this approach on available standard dataset yielding promising result. Exact traffic
estimate in a retail store require correct separation of customers from service
providers. We present a role based human classification framework using Gaussian
mixture model for this task. A novel feature descriptor named graded colour
histogram is defined for object representation. Using, our role based human
classification and tracking system, we have defined a novel computationally
efficient framework for two types of analytics generation i.e., region specific people
count and dwell-time estimation. This system has been extensively evaluated and
tested on four hours of real-life video captured from a retail store.
Index Terms—Human detection and tracking, Video Analytics
An Improved Bayesian Matting Method Based on Image statistic characteristics
Wei Sun, Siwei Luo, Lina Wu
School of Computer Science and Information Technology, Beijing Jiaotong
University, China
IP099
Abstract—Image matting is an important task in image and video editing and has
been studied for more than 30 years. In this paper we propose an improved
interactive matting method. Starting from a coarse user-guided trimap, we first
perform a color estimation based on texture and color information and use the result
to refine the original trimap. Then with the new trimap, we apply soft matting
process which is improved Bayesian matting with smoothness constraints.
Experimental results on natural image show that this method is useful, especially for
the images have similar texture feature in the background or the images which is
hard to give a precise trimap.
Index Terms—image matting, texture information, trimap
Session V–Authors’ Oral Presentation
(ICGIP 2014)--- 3D reconstruction and visualization
13:00pm-15:30pm,16:00pm-18:00pm
Session Chair: Prof. Godfried T. Toussaint, New York University Abu Dhabi, United
Arab Emirates
The 2014 IACSIT Beijing Conferences
Opening Presentation(IP204)
Measuring the Complexity of Binary Patterns: Kolmogorov Complexity versus
Subsymmetries
Godfried T. Toussaint
New York University Abu Dhabi, United Arab Emirates
IP204
Abstract—A simple mathematical measure of binary pattern complexity based on
sub-symmetries possessed by the patterns, originally proposed by C. Alexander and
S. Carey, is compared with a computationally feasible approximation of the Kolmog
orov complexity proposed by F. Papentin & M. Krüger, in terms of the effectiveness
with which the measures predict empirical measures and human judgments of patter
ncomplexity, as well as with regards to their computational complexity. The results
of experiments with binary images show that for small patterns it is difficult to explo
it the hierarchy of languages proposed by Papentin & Krüger for the approximation
of the Kolmogorov complexity. Furthermore, the Alexander-Carey measure exhibits
higher correlation with the empirical measures and human judgments. In addition, ex
perimental results show that the Alexander-Carey measure also predicts human judg
ments of complexity with two data sets in the aural domain with musical rhythms, th
us providing a connecting bridge between visual and auditory information processin
g
IndexTerms—binary patterns, visual patterns, auditory patterns, subsymmetries, Ale
xander-Carey complexity, Papentin complexity, Kolmogorov complexity, image pro
cessing, computer vision, computational music
A New Improved Local Chan-Vese Model
Wu Yiping, Shen Ming
College of Mathematics and Computer Science, Fuzhou University, China
IP005
IP016
Abstract—Based on the local image information, we propose a new improved
local active contour model to segment inhomogeneous images. The level set
evolution equation of the proposed model which is different from improved
Chan-Vese (ICV) model and local Chan-Vese (LCV) model is ordinary differential
equation. Without mean curvature and other complicate difference items, the
implementation becomes simpler by employing a finite difference scheme, thus the
efficiency of global segmentation is dramatically improved. Experimental results on
synthetic images as well as real medical images are shown in the paper to
demonstrate the segmentation accuracy, efficiency and robustness of the proposed
method.
Index Terms—Image segmentation, inhomogeneous, active contour model, ordinary
differential equation
Towards Relative Gradient and Its Applications
Yang Wang, Hongzhi Liu, Zhonghai Wu
Institute of Electronics, Chinese Academy of Sciences, China
The 2014 IACSIT Beijing Conferences
Abstract—Image gradients which present directional changes of pixel values in
an image are widely considered as important clues for salient features like edges.
However, it is difficult to distinguish edges from details which also have large
gradients merely based on gradients. In this paper, we propose a novel model called
relative gradient which can overcome the problem and better distinguish edges from
flat regions and details. We demonstrate the effectiveness of our model by
improving some representative algorithms using the relative gradient instead of
traditional gradient in contexts of edge detection and non-linear filtering. More
applications can be found in image processing, analysis and related tasks.
Index Terms—Relative gradient, edge detection, non-linear filtering
Learning Historical Heritage with a Serious Game: A User Study of Heerlen Roman
Bathhouse
Wen Qi
Open University Nederland, Heerlen, The Netherlands
IP017
Abstract—The advances of computer games have shown their potentials for
developing edutainment content and services. Current cultural heritages often make
use of games in order to complement existing presentations, to create a memorable
exhibition. It offers opportunities to reorganize and conceptualize historical, cultural
and technological information or knowledge about the exhibits. To demonstrate the
benefits of serious games in terms of facilitating the learning activities in a
constructive and meaningful way, we designed a video game about the Heerlen
Roman bathhouse heritage. This paper explains the design considerations of this
Roman bathhouse game, with a particular focus on the link between game play and
learning. In addition, we have carried out a user study to observe and measure the
learning effects of this game. Both quantitative and qualitative data are collected to
analyze the performance of the learners. The results have shown that this game
indeed can help learners understand the important historical facts and the related
knowledge of the heritage being studied. Further directions include converting the
first-person game into a third-person or multiple players’ game.
Index Terms—cultural heritage, Roman Bathhouse, pedagogy, serious game design
Crystallization Mosaic Effects Generation via Superpixels
Yuqi Xie, Pengbo Bo, Ye Yuan, Kuanquan Wang
School of Computer Science and Technology, Harbin Institute of Technology, China
IP021
Abstract—Art effect generation from digital images using computational tools has
been a hot research topic in recent years. We propose a new method for generating
crystallization mosaic effects from color images. Two key problems in generating
pleasant mosaic effect are studied: grouping pixels into mosaic tiles and arrangement
of mosaic tiles adapting to image features. To give visually pleasant mosaic effect,
The 2014 IACSIT Beijing Conferences
we propose to create mosaic tiles by pixel clustering in feature space of color
information, taking compactness of tiles into consideration as well. Moreover, we
propose a method for processing feature boundaries in images which gives guidance
for arranging mosaic tiles near image features. This method gives nearly uniform
shape of mosaic tiles, adapting to feature lines in an esthetic way. The new approach
considers both color distance and Euclidean distance of pixels, and thus is capable of
giving mosaic tiles in a more pleasing manner. Some experiments are included to
demonstrate the computational efficiency of the present method and its capability of
generating visually pleasant mosaic tiles. Comparisons with existing approaches
are also included to show the superiority of the new method.
Index Terms—Mosaic effect, superpixel, image segmentation, Voronoi diagram
Block-matching 3-D Transform Based Multi-focus Image Fusion
Feng Zhu, Yingkun Hou, Minxian Li, Jingyu Yang
School of Computer Science and Engineering, Nanjing University of Science and
Technology, China
IP024
Abstract—Block matching 3-D transform (BM3D) is an excellent image
denoising algorithm, the success of this algorithm is that it makes full use of the
image self-similarity. Profiting from the superior performance of the BM3D, this
paper propose a multi-focus image fusion algorithm. A pair of the original images
are both implemented BM3D respectively, averaging their low frequency
coefficients can get the low frequency coefficient of the result image, the bigger high
frequency coefficient in these two transforms is chosen as the high frequency
coefficient of the result image; Implementing inverse 3-D transformation can obtain
the fused image. Experimental results show that the proposed algorithm is better
than the existing multi-focus image fusion algorithms on both the subjective visual
and the objective evaluation.
Index Terms—Image fusion, block-matching, 3-D transform
Satellite Image Scene Classification Using Spatial Information
Weiwei Song, Dunwei Wen,Ke Wang, Tong Liu and Mujun Zang
College of Communication Engineering, Jilin University, Changchun, Jilin, China
IP052
Abstract—In order to enhance the local feature’s describing capacity and improve
the classification performance of high-resolution (HR) satellite images, we present
an HR satellite image scene classification method that make use of spatial
information of local feature. First, the spatial pyramid matching model (SPMM) is
adopted to encode spatial information of local feature. Then, images are represented
by the local feature descriptors and encoding information. Finally, the support vector
machine (SVM) classifier is employed to classify image scenes. The experiment
results on a real satellite image dataset show that our method can classify the scene
classes with an 82.6% accuracy, which indicates that the method can work well on
describing HR satellite images and classifying different scenes.
Index Terms—Satellite image, spatial pyramid model, spatial information, support
The 2014 IACSIT Beijing Conferences
vector machine
Attitude measurement by using target schlieren graph and 3D digital model in wind
tunnel
CHENG Lei, YANG Yinong, XUE Bindang,ZHOU Fugen and BAI Xiangzhi
School of Astronautics, Beihang University, China
IP068
Abstract—Schlieren photography is normal device in wind tunnel. It records
varying density of flow and also shows the attitude of model. In this paper, a method
is proposed to estimate the model attitudes through matching the projection
drawings of 3D digital model with the schlieren photography and high speed camera
image. A simulation experiment is also designed to test the method. The results
show that the maximum error less than 0.1°.We also use the method to deal with the
wind tunnel test data, and experimental results show that the proposed system can
meet the demands of the wind tunnel test.
Index Terms—Attitude measurement, Schlieren graph, Image Matching, Wind
tunnel
3D Reconstruction and Visualization of Plant Leaves
Xiaomeng Gu, Lihong Xu,,Dawei Li, and Peng Zhang
College of Electronics and Information Engineering, Tongji University, China
IP072
Abstract—In this paper, a three-dimensional reconstruction method, which is
based on point clouds and texture images, is used to realize the visualization of
leaves of greenhouse crops. We take Epipremnum aureum as the object for study and
focus on applying the triangular meshing method to organize and categorize
scattered point cloud input data of leaves, and then construct a triangulated surface
with interconnection topology to simulate the real surface of the object. At last we
texture-map the leaf surface with real images to present a life-like 3D model which
can be used to simulate the growth of greenhouse plants.
Index Terms—visualization, triangulated meshing method, 3D reconstruction,
greenhouse plants.
Improved stereo matching applied to digitization of greenhouse plants
Peng Zhang, Lihong Xu, Dawei Li, Xiaomeng Gu
College of Electronics and Information Engineering, Tongji University, China
IP073
Abstract—The digitization of greenhouse plants is an important aspect of digital
agriculture. Its ultimate aim is to reconstruct a visible and interoperable virtual plant
model on the computer by using state-of-the-art image process and computer
graphics technologies. The most prominent difficulties of the digitization of
greenhouse plants include how to acquire the three-dimensional shape data of
greenhouse plants and how to carry out its realistic stereo reconstruction.
Concerning these issues an effective method for the digitization of greenhouse plants
The 2014 IACSIT Beijing Conferences
is proposed by using a binocular stereo vision system in this paper. Stereo vision is a
technique aiming at inferring depth information from two or more cameras; it
consists of four parts: calibration of the cameras, stereo rectification, search of stereo
correspondence and triangulation. Through the final triangulation procedure, the 3D
point cloud of the plant can be achieved. The proposed stereo vision system can
facilitate further segmentation of plant organs such as stems and leaves; moreover, it
can provide reliable digital samples for the visualization of greenhouse tomato
plants.
Index Terms—digitization, greenhouse plants, stereo matching, binocular stereo
vision
An efficient framework for modeling clouds from Landsat8 images
Chunqiang Yuan
Beihang University, Beijing, China
IP083
Abstract—Cloud plays an important role in creating realistic outdoor scenes for
video game and flight simulation applications. Classic methods have been proposed
for cumulus cloud modeling. However, these methods are not flexible for modeling
large cloud scenes with hundreds of clouds in that the user must repeatedly model
each cloud and adjust its various properties. This paper presents a meteorologically
based method to reconstruct cumulus clouds from high resolution Landsat8 satellite
images. From these input satellite images, the clouds are first segmented from the
background. Then, the cloud top surface is estimated from the temperature of the
infrared image. After that, under a mild assumption of flat base for cumulus cloud,
the base height of each cloud is computed by averaging the top height for pixels on
the cloud edge. Then, the extinction is generated from the visible image. Finally, we
enrich the initial shapes of clouds using a fractal method and represent the recovered
clouds as a particle system. The experimental results demonstrate our method can
yield realistic cloud scenes resembling those in the satellite images.
Index Terms—satellite image, cumulus cloud, three-dimensional reconstruction,
particle system
An artificial target location method for curiosity rover
LI Ying, PENG Jing, DU Ying
China Academy of Space Technology, China
IP092
Abstract—Template matching is a common method for object recognition and
location. But the premise of template matching is the target should not change a lot
in shape from the template image. When non-coplanar rotation exits, the traditional
template matching method is helpless. By analyzing the artificial target of the
curiosity rover, a two-step artificial target location method is proposed. Firstly, least
squares ellipse fitting method is used to recognize the artificial target in the image
and locate the center of each ellipse preliminary. Secondly, according to the
preliminary result of ellipse fitting, the image is graph cut into pieces, and each
piece only has one ellipse. Then Hough transform is used to locate the center of the
artificial target precisely. Meanwhile, before edge detection, mathematical
The 2014 IACSIT Beijing Conferences
morphology technology is conducted to remove the influence of the shadow in the
image. Otsu algorithm is used to choose the threshold value of canny edge detector
adaptively. Experiments are carried out based on artificial target images of curiosity
rover, which show that the robustness of the algorithm in non-ideal illumination
situation. The location accuracy is within 1 pixel.
Index Terms—Hough transform, artificial target location, curiosity rover, ellipse
fitting
An Optimizing Processing Approach to Contrast Correction Based on Nonlinear
Mapping of Windowed Tone
Ming Gao, Shiyin Qin
School of Automation Science and Electrical Engineering, Beihang University,
China
IP093
Abstract—A contrast correction method is presented based on nonlinear mapping
of windowed tone. The main idea of method is to employ the local nonlinear
mapping model on the small size with overlapping windows of traversal the whole
image. At first, a high dynamic range (HDR) image contrast correction is introduced,
and then through the formula deduction, a model for decision optimization of
contrast correction is established, in which some constraints are termed as two
adaptive guided images based on human visual properties so as to improve the
optimal solution. Finally, the optimal contrast correction can be implemented by
solving the optimizing processing problem through a linearized reduction. A series
of experiments with the HDR natural images are carried out and the results of
objective quality metrics have showed that the proposed method can effectively
improve and optimize the contrast correction to outperform those current existing
methods.
Index Terms—contrast correction, nonlinear mapping, adaptive guided images,
optimizing processing
Learning Self-adaptive Color Harmony Model For Aesthetic Quality Classification
Zhijie Kuang , Peng Lu, Xiaojie Wang
Beijing University of Posts and Telecommunications, China
IP097
Abstract—Color harmony is one of the key aspects in aesthetic quality classification
for photos. The existing color harmony models either are in lack of quantization
schemes or can assess simple color patterns only. Therefore, these models cannot be
applied to assess color harmony of photos directly. To address this problem, we
proposed a simple data-based self-adaptive color harmony model. In this model, the
hue distribution of a photo is fitted by mean shift based method, then features are
extracted according to this distribution and finally the Gaussian mixture model is
applied for learning features extracted from all the photos. The experimental results
on eight categories datasets show that the proposed method outperforms the classic
rule-based methods and the state-of-the-art data-based model.
The 2014 IACSIT Beijing Conferences
Index Terms—Aesthetics, mean shift, color harmony, image quality, GMM
A robust method for estimating motorbike count based on visual information
learning
Chi-Kien HUYNH\, THAI N. Dung, LE Thanh Sach, THOAI Nam, Kazuhiko
HAMAMOTO
HCMC University of Technology, Vietnam
IP0103
Abstract—Estimating the number of vehicles in traffic videos is an important and
challenging task in traffic surveillance, especially with a high level of occlusions
between vehicles, e.g.in crowded urban area with people and/or motorbikes. In such
the condition, the problem of separating individual vehicles from foreground
silhouettes often requires complicated computation [1][2][3]. Thus, the counting
problem is gradually shifted into drawing statistical inferences of target objects
density from their shape [4], local features [5], etc. Those researches indicate a
correlation between local features and the number of target objects. However, they
are inadequate to construct an accurate model for vehicles density estimation. In this
paper, we present a reliable method that is robust to illumination changes and partial
affine transformations. It can achieve high accuracy in case of occlusions. Firstly,
local features are extracted from images of the scene using Speed-Up Robust
Features (SURF) method. For each image, a global feature vector is computed using
a Bag-of-Words model which is constructed from the local features above. Finally, a
mapping between the extracted global feature vectors and their labels (the number of
motorbikes) is learned. That mapping provides us a strong prediction model for
estimating the number of motorbikesin new images. The experimental results show
that our proposed method can achieve a better accuracy in comparison to others.
Index Terms—Crowd analysis, SURF, Bag-of-Words, motorbike counting, traffic
density estimation
Design of 3D Simulation Engine for Oilfield Safety Training
Li Hua-Ming, Kang Bao-Sheng
College of Information Science and Technology, China
IP201
Abstract—Aiming at the demand for rapid custom development of 3D simulation
system for oilfield safety training, this paper design and implement a 3D simulation
engine based on script-driven method, multi-layer structure, pre-defined entity
objects and high-level tools such as scene editor, script editor, program loader. A
scripting language been defined to control the system's progress, events and
operating results. Training teacher can use this engine to edit 3D virtual scenes, set
the properties of entity objects, define the logic script of task, and produce a 3D
simulation training system without any skills of programming. Through expanding
entity class, this engine can be quickly applied to other virtual training areas.
Index Terms—3D simulation engine, script-driven method, entity objects, safety
training
The 2014 IACSIT Beijing Conferences
Poster Presentation
13:10pm-18:00pm
Stereo Vision-Based Pedestrian Detection Using Dense Disparity Map- Based
Detection and Segmentation
Chung-Hee Lee, Dongyoung Kim
Daegu Gyeongbuk Institute of Science & Technology(DGIST), Daegu, KOREA
IP035
Abstract—In this paper, we propose a stereo vision-based pedestrian detection
method using a dense disparity map-based detection and segmentation algorithm. To
enhance a pedestrian detection performance, we use a dense disparity map extracted
from a global stereo matching algorithm. First, we extract a road feature information
from the dense disparity map, which is a decision basis of presence or absence of
obstacles on the road. It is very important to extract the road feature from the
disparity for detecting obstacles robustly regardless of external traffic situations. The
obstacle detection is performed with the road feature information to detect only
obstacles from entire image. In other words, pedestrian candidates including various
upright objects are detected in the obstacle detection stage. Each obstacle area tends
to include multiple objects. Thus, a disparity map-based segmentation is performed
to separate the obstacle area into each obstacle accurately. And then, accurate
pedestrian areas are extracted from segmented obstacle areas using road contact and
pedestrian height information. This stage enables to reduce false alarms and to
enhance computing speed. To recognize pedestrians, classifier is performed in each
verified pedestrian candidate. Finally, we perform a verification stage to examine the
recognized pedestrian in detail. Our algorithms are verified by conducting
experiments using ETH database.
Index Terms—dense disparity map, stereo vision, pedestrian, segmentation,
detection
Barcode Localization With Region-Based Gradien t Statistical Analysis
Zhiyuan Chen, Yuming Zhao
Shanghai Jiao Tong University, China
IP041
Abstract—Barcode, as a kind of data representation method, has been adopted in a
wide range of areas. Especially with the rise of the smart phone and the hand-held de
vice equipped with high resolution camera and great computation power, barcode tec
hnique has found itself more extensive applications. In industrial field, barcode readi
ng system is highly demanded to be robust to blur, illumination change, pitch, rotatio
n, and scale change. This paper gives a new idea in localizing barcode under a regio
The 2014 IACSIT Beijing Conferences
n-based gradient statistical analysis. Making this idea as the basis, four algorithms h
ave been developed for dealing with Linear, PDF417, Stacked 1D1D and Stacked 1
D2D barcodes respectively. After being evaluated on our challenging dataset with m
ore than 17000 images, the result shows that our methods can achieve an average loc
alization accuracy of 82.17% with respect to 8 kinds of distortions and within an ave
rage time of 12 ms.
Index Terms—barcode localization, region-based gradient statistical analysis,
vertices finding
The 2014 IACSIT Beijing Conferences
About Keynote Speaker:
Keynote Speaker I
Prof. David Zhang
Hong Kong Polytechnic University，Hong Kong
Prof. David Zhang graduated in Computer Science from Peking University. He
received his MSc in 1982 and his PhD in 1985 in Computer Science from the Harbin
Institute of Technology (HIT), respectively. From 1986 to 1988 he was a Postdoctoral
Fellow at Tsinghua University and then an Associate Professor at the Academia
Sinica, Beijing. In 1994 he received his second PhD in Electrical and Computer
Engineering from the University of Waterloo, Ontario, Canada. He is a Head,
Department of Computing (2008-10) and Chair Professor since 2005 at the Hong Kong
Polytechnic University where he is the Founding Director of the Biometrics
Technology Centre (UGC/CRC) supported by the Hong Kong SAR Government in
1998. He also serves as Visiting Chair Professor in Tsinghua University, and Adjunct
Professor in Peking University, Shanghai Jiao Tong University, HIT, and the
University of Waterloo. He is the Founder and Editor-in-Chief, International Journal of
Image and Graphics (IJIG); Book Editor, Springer International Series on Biometrics
(KISB); Organizer, the International Conference on Biometrics Authentication (ICBA);
Associate Editor of more than ten international journals including IEEE Transactions
and so on; and the author of more than 10 books,over 250 international journal
papers and around 30 patents from USA/Japan/HK/China. According to Science
Citation Index (SCI)- Expended and Google Scholar, his papers have got over 8,000
citations and 18,000 citations, respectively. Professor Zhang is recognized as a world
leading expert in biometrics, specially palmprint recognition. He is a Croucher Senior
Research Fellow, Distinguished Speaker of the IEEE Computer Society, and a Fellow
of both IEEE and IAPR.
The 2014 IACSIT Beijing Conferences
Keynote Speaker II
Prof. Xudong Jiang
Nanyang Technological University
Xudong Jiang received the B.Eng. and M.Eng. degree from the University of
Electronic Science and Technology of China, Chengdu, China in 1983 and 1986,
respectively, and received the Ph.D. degree from the Helmut Schmidt University
Hamburg, Germany in 1997, all in electrical and electronic engineering.
From 1986 to 1993, he worked as Lecturer at the University of Electronic Science and
Technology of China where he received two Science and Technology Awards from
the Ministry for Electronic Industry of China. He was a recipient of the German
Konrad-Adenauer Foundation young scientist scholarship. From 1993 to 1997, he was
with the Helmut Schmidt University Hamburg, Germany as scientific assistant. From
1998 to 2002, He worked with the Centre for Signal Processing (CSP), Nanyang
Technological University, Singapore, first as Research Fellow and then as Senior
Research Fellow, where he developed a fingerprint verification algorithm that
achieved the fastest and the second most accurate fingerprint verification in the
International Fingerprint Verification Competition (FVC2000). From 2002 to 2004 he
worked as Lead Scientist and appointed as the Head of Biometrics Laboratory at the
Institute for Infocomm Research, A*Star, Singapore. From 2002 to 2004 he was an
Adjunct Assistant Professor. and joined NTU as a full time faculty member in 2004.
Currently, Dr Jiang is an Associate Professor (tenured) of School of Electrical and
Electronic Engineering, Nanyang Technological University and is appointed as
Director of Centre for Information Security (CIS).
Dr Jiang has published over seventy research papers in international refereed
journals and conferences. He is also an inventor of one PCT patent application, three
Singapore patents and three United States patents, some of which were
commercialized. Dr Jiang is a senior member of IEEE and has been serving as
Editorial Board Member, Guest Editor and Reviewer of multiple international journals,
and serving as Program Committee member, Keynote Speaker and Session Chair of
multiple international conferences. His research interest includes pattern recognition,
computer vision, image and signal processing, biometrics, face recognition and
fingerprint recognition.
The 2014 IACSIT Beijing Conferences
Keynote Speaker III
Prof. Ming Yang,
Southern Polytechnic State University, USA
Dr. Ming Yang is currently an Associate Professor with School of Computing and
Software Engineering, Southern Polytechnic State University, USA. He obtained his
BS and MS degrees in Electrical Engineering from Tianjin University (Tianjin, China)
in 1997 and 2000 respectively, and his Ph.D. degree in Computer Science and
Engineering from Wright State University (Dayton, Ohio, USA) in 2006. His research
interests include Information Security, Multimedia Communication, and Mobile
Security. He is the author/co-author of over fifty peer-reviewed journal, conference,
and book chapter publications. His research has been supported by US National
Science Foundation and Computing Research Association. He is currently serving
the Co-Editor-in-Chief of International Journal of Monitoring and Surveillance
Technology Research.
The 2014 IACSIT Beijing Conferences
Conference Venue
JIANGXI GRAND HOTEL
http://www.bjjxhotel.com/index_en.php
ADD: NO.8 Hengyitiao, Feng Tai District, Beijing , China
4 Boulevard Berthier, 17. Palais des Congrès - Batignolles, 75017 Paris
TEL: 0086---10-6760 8866
FAX: 0086---10-8767 7728
The 2014 IACSIT Beijing Conferences
Upcoming Conferences Information:
Welcome to Our More Upcoming Conferences in 2014:
DATE
NAME
PAPER WILL BE PUBLISHED BY
Applied Mechanics and Materials Journal
(ISSN: 1660-9336)
Dec 18-20,
2014
Barcelona,
Spain
ICPSE 2014
2014
3rd
International
Conference on
Power
Science and Engineering
http://www.icpse.org/
ICNB 2014
2014
5th
International
Conference
on
Nanotechnology
and
Biosensors
http://www.icnb.org/
ICMPM 2014
2014
Conference
Mechanical
Materials
International
on
Properties of
http://www.icmpm.org/
Indexed by Elsevier: SCOPUS www.scopus.com and Ei
Compendex (CPX) www.ei.org. Cambridge Scientific
Abstracts (CSA) www.csa.com, Chemical Abstracts (CA)
www.cas.org, Google and Google Scholar google.com,
ISI (ISTP, CPCI, Web of Science) www.isinet.com,
Institution of Electrical Engineers (IEE) www.iee.org, etc
Applied Mechanics and Materials Journal
(ISSN: 1660-9336)
Indexed by Elsevier: SCOPUS www.scopus.com and Ei
Compendex (CPX) www.ei.org. Cambridge Scientific
Abstracts (CSA) www.csa.com, Chemical Abstracts (CA)
www.cas.org, Google and Google Scholar google.com,
ISI (ISTP, CPCI, Web of Science) www.isinet.com,
Institution of Electrical Engineers (IEE) www.iee.org, etc.
Applied Mechanics and Materials Journal
(ISSN: 1660-9336)
Indexed by Elsevier: SCOPUS www.scopus.com and Ei
Compendex (CPX) www.ei.org. Cambridge Scientific
Abstracts (CSA) www.csa.com, Chemical Abstracts (CA)
www.cas.org, Google and Google Scholar google.com,
ISI (ISTP, CPCI, Web of Science) www.isinet.com,
Institution of Electrical Engineers (IEE) www.iee.org, etc.
All accepted papers will be published in one of
the indexed Journals after being selected.
Journal of Computers (JCP, ISSN: 1796-203X, 20 Papers)
ICCNE 2014
Dec 22-24,
2014
Barcelona,
Spain
2014
International
Conference
on
Communications
and
Network Engineering
Journal of Software (JSW, ISSN: 1796-217X, 20 Papers)
International Journal of Future Computer and
Communication (IJFCC, ISSN: 2010-3751, 30 Papers)
http://www.iccne.org/
International Journal of Computer and Communication
Engineering (IJCCE, ISSN: 2010-3743, 30 Papers)
ICOAI2014
2014
International
Conference on
Artificial
Intelligence
http://www.icoai.org/
Journal of Advances in Computer Networks (JACN,
ISSN: 1793-8244, 20 Papers)
International Journal of Machine Learning and
Computing (IJMLC
ISSN: 2010-3700)
Abstracting/ Indexing: Engineering & Technology Digital
Library, Google Scholar, Crossref, ProQuest, Electronic
Journals Library, DOAJ and EI (INSPEC, IET).
The 2014 IACSIT Beijing Conferences
All accepted papers will be published in one of
the indexed Journals after being selected.
Journal of Computers (JCP, ISSN: 1796-203X, 20 Papers)
Journal of Software (JSW, ISSN: 1796-217X, 20 Papers)
Journal of Communications(JCM,
1796-2021, 20 papers)
ISSN:
ISSN:
International Journal of Future Computer and
Communication (IJFCC, ISSN: 2010-3751, 30 Papers)
ICCSIT 2014
2014
7th
International
Conference on
Computer
Science and Information
Technology
http://www.iccsit.org/
International Journal of Computer Theory and
Engineering (IJCTE, ISSN: 1793-8201, 30 Papers)
International Journal of Computer and Electrical
Engineering (IJCEE, ISSN: 1793-8163, 30 Papers)
International Journal of Information and Electronics
Engineering (IJIEE, ISSN: 2010-3719, 20 Papers)
International Journal of Information and Education
Technology (IJIET, ISSN: 2010-3689, 20 Papers)
Journal of Advances in Computer Networks (JACN,
ISSN: 1793-8244, 20 Papers)
Lecture Notes on Software Engineering (LNSE, ISSN:
2301-3559, Papers)
Welcome to Our More Upcoming Conferences in 2015:
ICSST 2015
2015 the 4th International
Conference on Security Science
and Technology
http://www.icsst.org/
Jan 15-16,
2015
Portsmouth,
UK
ICNCS 2015
2015 the 4th International
Conference on Network and
Computer Science
http://www.icncs.org/
ICK 2015
2015 International Conference
on Knowledge
http://www.ick.org/
All accepted papers will be published in the volume
of International Journal of Engineering and
Technology (IJET) (ISSN; 1793-8244 (Online Version);
1793-8236 (Print Version))
All accepted papers will be published in the volume
of International Journal of Future Computer and
Communication (IJFCC) (ISSN: 2010-3751)
Abstracting/ Indexing: Google Scholar, Engineering &
Technology
Digital
Library,
and
Crossref, DOAJ, Electronic Journals Library, EI (INSPEC,
IET).
All accepted papers will be published in the volume
of International Journal of Knowledge Engineering
(IJKE)
The 2014 IACSIT Beijing Conferences
All accepted papers of ICMM 2015 will be
published by Applied Mechanics and Materials
Journal (ISSN: 1660-9336).
Feb 12-13,
2015
Busan,
South Korea
ICMM 2015
2015
6th
International
Conference on Mechatronics
and Manufacturing
http://www.icmm.org/
ICAEE 2015
2015 the 2nd International
Conference on Advances in
Electronics Engineering
http://www.icaee.org/
ICAPM 2015
2015
5th
International
Conference on Applied Physics
and Mathematics
http://www.icapm.org/

ICMLC 2015
Mar19-20,
2015
Florence,
Italy
2015
7th
International
Conference
on
Machine
Learning and Computing
http://www.icmlc.org/
ICEIT 2015
2015
4th
International
Conference on Educational and
Information Technology
http://www.iceit.org/
ICICN 2015
2015
3rd
International
Conference on Information
and Computer Networks
http://www.icicn.org/
Indexed by Elsevier: SCOPUS www.scopus.com and Ei
Compendex (CPX) www.ei.org. Cambridge Scientific
Abstracts (CSA)www.csa.com, Chemical Abstracts
(CA) www.cas.org, Google and Google Scholar
google.com,
ISI
(ISTP,
CPCI,
Web
of
Science) www.isinet.com, Institution of Electrical
Engineers (IEE) www.iee.org, etc.
All accepted papers of ICAEE 2015 will be published
by International Journal of Information and
Electronics Engineering (IJIEE) (ISSN: 2010-3719)
Indexed by Google Scholar, Electronic Journals
Library,Engineering
&
Technology
Digital
Library,Crossref and ProQuest, DOAJ, Ei (INSPEC, IET).
All accepted papers of ICAPM 2015 will be published
by International Journal of Applied Physics and
Mathematics (IJAPM) (ISSN: 2010-362X)
Indexed by EI (INSPEC, IET),Chemical Abstracts
Services
(CAS), DOAJ,Electronic
Journals
Library, Engineering & Technology Digital Library,
Nanowerk Database, Crossref, Google Scholar and
ProQuest.
All accepted papers of ICMLC 2015 will be published
by International Journal of Machine Learning and
Computing (IJMLC) (ISSN: 2010-3700)
Indexed by Engineering & Technology Digital Library,
Google Scholar, Crossref, ProQuest, Electronic Journals
Library, DOAJ and EI (INSPEC, IET).
All accepted papers of ICEIT 2015 will be published
by Journal of Information and Education Technology
(IJIET). (ISSN: 2010-3689)
Indexed
by
EI
(INSPEC,
IET),Cabell's
Directories, DOAJ, Electronic
Journals
Library,
Engineering & Technology Digital Library, EBSCO,
Google Scholar, Crossref and ProQuest.
All accepted papers of ICICN 2015 will be published
by
Journal
of
Advances
in
Computer
Networks (ISSN: 1793-8244)
Indexed by Engineering & Technology Digital
Library, EBSCO, DOAJ, Electronic Journals Library,
Ulrich's Periodicals Directory, International Computer
Science Digital Library (ICSDL), ProQuest, and Google
Scholar.
The 2014 IACSIT Beijing Conferences
ICTLE 2015
2015
4th
International
Conference on Traffic and
Logistic Engineering
http://www.ictle.org/
ICCEB 2015
2015
4th
International
Conference
on
Computer
Engineering
and
Bioinformatics
http://www.icceb.org/
ICFD 2015
2015 International Conference
on Fluid Dynamics
http://www.icfd.org/
April 6-7,
2015
Orlando,
USA
All accepted papers of ICTLE 2015 will be published
by Journal
of
Traffic
and
Logistics
Engineering (JTLE) (ISSN: 2301-3680)
Indexed by Ulrich's Periodicals Directory, Google
Scholar, EBSCO, Engineering & Technology Digital
Library and Electronic Journals Digital Library.
All accepted papers of ICCEB 2015 will be published
by International Journal of Engineering and
Technology (IJET) (ISSN: 1793-8236).
Indexed
by
Chemical
Abstracts
Services
(CAS), DOAJ, Engineering & Technology Digital Library,
Google Scholar, Ulrich Periodicals Directory, Crossref,
ProQuest, Electronic
Journals
Library, Index
Copernicus, EI (INSPEC, IET).
All accepted papers of ICFD 2015 will be published by
Applied Mechanics and Materials Journal (ISSN:
1660-9336)
Indexed by Elsevier: SCOPUS www.scopus.com and Ei
Compendex (CPX) www.ei.org. Cambridge Scientific
Abstracts (CSA)www.csa.com, Chemical Abstracts
(CA) www.cas.org, Google and Google Scholar
google.com,
ISI
(ISTP,
CPCI,
Web
of
Science) www.isinet.com, Institution of Electrical
Engineers (IEE) www.iee.org, etc.
The 2014 IACSIT Beijing Conferences
All accepted papers of ICEEE 2015 will be published
in the one of the following Journal with ISSN.
Applied Mechanics and Materials Journal (ISSN:
1660-9336)
Indexed by Elsevier: SCOPUS www.scopus.com and Ei
Compendex (CPX) www.ei.org. Cambridge Scientific
Abstracts (CSA)www.csa.com, Chemical Abstracts (CA)
www.cas.org, Google and Google Scholar google.com,
ISI (ISTP, CPCI, Web of Science) www.isinet.com,
Institution of Electrical Engineers (IEE) www.iee.org,
etc.
ICEEE 2015
2015
2nd
International
Conference on Electrical and
Electronics Engineering
http://www.iceee.org/
International Journal of Electronics and Electrical
Engineering (ISSN: 2301-380X)
Indexed by Ulrich's Periodicals Directory, Google
Scholar, EBSCO, Engineering & Technology Digital
Library, etc.
Journal of Automation and Control Engineering
(ISSN: 2301-3702)
Indexed by EI (INSPEC, IET), Ulrich's Periodicals
Directory, Google Scholar, EBSCO, Engineering &
Technology Digital Library and etc.
International Journal of Electrical Energy (ISSN:
2301-3656)
Indexed by EI(INSPEC, IET), Ulrich's Periodicals
Directory, Google Scholar, EBSCO, Engineering &
Technology Digital Library and etc.
All accepted papers of ICCIT 2015 will be published in
the one of the following Journal with ISSN.
Journal of Software (JSW, ISSN 1796-217X)
April 28-29,
2015
Ankara,
Turkey
ICCIT 2015
2015 International Conference
on Computer and Information
Technology
http://www.iccit.org/
International Journal of Computer Theory and
Engineering (IJCTE) (ISSN: 1793-8201)
Indexed by Index Copernicus, Electronic Journals
Library, EBSCO, Engineering & Technology Digital
Library, Google Scholar, Ulrich's Periodicals Directory,
Crossref, ProQuest, WorldCat, and EI (INSPEC, IET),
Cabell's Directories.
International Journal of Computer and Electrical
Engineering (IJCEE) (ISSN: 1793-8163)
Indexed by Ulrich's Periodicals Directory, Google
Scholar, EBSCO, Engineering & Technology Digital
Library, Crossref, ProQuest, EI (INSPEC, IET), and
Electronic Journals Library
Lecture Notes on Information Theory (ISSN:
2301-3788)
Indexed by EI(INSPEC, IET), Ulrich's Periodicals
Directory, Google Scholar, EBSCO, Engineering &
Technology Digital Library and etc.
The 2014 IACSIT Beijing Conferences
All accepted papers of IOAC 2015 will be published
by Applied Mechanics and Materials Journal (ISSN:
1660-9336)
ICOAC 2015
2015 International Conference
on Automatic Control
http://www.icoac.org/
ICMML 2015
2015 6th International
Conference on 2015 6th
International Conference on
Material and Manufacturing
Technology
http://www.icmml.org/
May 9-10,
2015
Bali,
Indonesia
ICRE 2015
2015 International Conference
on Reliability Engineering
http://www.icre.org/
Indexed by Elsevier: SCOPUS www.scopus.com and Ei
Compendex (CPX) www.ei.org. Cambridge Scientific
Abstracts (CSA)www.csa.com, Chemical Abstracts (CA)
www.cas.org, Google and Google Scholar google.com,
ISI (ISTP, CPCI, Web of Science) www.isinet.com,
Institution of Electrical Engineers (IEE) www.iee.org,
etc.
All accepted papers of ICMML 2015 will be published
by Advanced Materials Research (ISSN: 1022-6680).
Indexed by Elsevier: SCOPUSwww.scopus.com and Ei
Compendex (CPX) www.ei.org/. Cambridge Scientific
Abstracts (CSA) www.csa.com, Chemical Abstracts
(CA) www.cas.org, Google and Google Scholar
google.com,
ISI
(ISTP,
CPCI,
Web
of
Science) www.isinet.com , Institution of Electrical
Engineers (IEE)www.iee.org , etc
All accepted papers of ICRE 2015 will be published in
the one of the following Journal with ISSN.
Advanced Materials Research (ISSN: 1022-6680).
Indexed by Elsevier: SCOPUSwww.scopus.com and Ei
Compendex (CPX) www.ei.org/. Cambridge Scientific
Abstracts (CSA) www.csa.com, Chemical Abstracts
(CA) www.cas.org, Google and Google Scholar
google.com,
ISI
(ISTP,
CPCI,
Web
of
Science) www.isinet.com , Institution of Electrical
Engineers (IEE)www.iee.org , etc
Journal of Engineering and Technology (IJET) (ISSN:
1793-8236).
Indexed
by
Chemical
Abstracts
Services
(CAS), DOAJ, Engineering & Technology Digital Library,
Google Scholar, Ulrich Periodicals Directory, Crossref,
ProQuest, Electronic
Journals
Library, Index
Copernicus, EI (INSPEC, IET).
All accepted papers of ICLB 2015 will be published by
Advanced Materials Research (ISSN: 1022-6680).
ICLB 2015
2015 International Conference
on Lithium Batteries
http://www.iclb.org/
Indexed by Elsevier: SCOPUSwww.scopus.com and Ei
Compendex (CPX) www.ei.org/. Cambridge Scientific
Abstracts (CSA) www.csa.com, Chemical Abstracts
(CA) www.cas.org, Google and Google Scholar
google.com,
ISI
(ISTP,
CPCI,
Web
of
Science) www.isinet.com , Institution of Electrical
Engineers (IEE)www.iee.org , etc
The 2014 IACSIT Beijing Conferences
All accepted papers of ICCSN 2015 will be published
in the one of the following Journal with ISSN.
WIT Transactions on Information and Communication
Technologies (ISSN: 1743-3517)
ICCSN 2015
2015 the 7th International
Conference on Communication
Software and Networks
http://www.iccsn.org/
Indexed by EI Compendex, Scopus and ISI.
Journal of Communications (JCM) (ISSN: 1796-2021;
DOI: 10.12720/jcm)
Indexed by EI Compendex; SCOPUS; ULRICH's
Periodicals Directory; Google Scholar; INSPEC; etc.
All accepted papers of ICIIP 2015 will be published in
the one of the following Journal with ISSN.
WIT Transactions on Information and Communication
Technologies (ISSN: 1743-3517)
June 6-7,
2015
Chengdu,
China
ICIIP 2015
2015 the 4th International
Conference on Intelligent
Information Processing
http://www.iciip.org/
Indexed by EI Compendex, Scopus and ISI.
Journal of Industrial and Intelligent Information
(ISSN: 2301-3745; DOI: 10.12720/jiii)
Indexed by EI(INSPEC, IET), Google Scholar, EBSCO,
Engineering & Technology Digital Library and etc.
All accepted papers of ICWOC 2015 will be published
in the one of the following Journal with ISSN.
WIT Transactions on Information and Communication
Technologies (ISSN: 1743-3517)
ICWOC
2015
2015 the 4th International
Conference on Wireless and
Optical Communications
http://www.icwoc.org/
ICDDM 2015
The 2015 4th International
Conference on Database and
Data Mining
http://www.icddm.org/
July 2-3,
2015
Chicago,
USA
ICKD 2015
The 2015 4th International
Conference on Knowledge
Discovery
http://www.ickd.org/
Indexed by EI Compendex, Scopus and ISI.
International Journal of Future Computer and
Communication (ISSN:
2010-3751;
DOI:
10.7763/IJFCC)
Indexed by Google Scholar, Engineering & Technology
Digital Library, and Crossref,DOAJ, Electronic Journals
Library, EI (INSPEC, IET).
All accepted papers of ICDDM 2015 will be published
by WIT Transactions on Information and
Communication Technologies (ISSN: 1743-3517)
Indexed by EI Compendex, Scopus and ISI.
All accepted papers of ICKD 2015 will be published by
International Journal of Computer Theory and
Engineering (IJCTE)(ISSN: 1793-8201)
Indexed by Electronic Journals Library, EBSCO,
Engineering & Technology Digital Library, Google
Scholar, INSPEC, Ulrich's Periodicals Directory, Crossref,
ProQuest, WorldCat, and EI(INSPEC, IET).
The 2014 IACSIT Beijing Conferences
ICOIP 2015
The 2015 4th International
Conference on Optoelectronics
and Image Processing
http://www.icoip.org/
All accepted papers of ICDDM 2015 will be published
by WIT Transactions on Information and
Communication Technologies (ISSN: 1743-3517)
Indexed by EI Compendex, Scopus and ISI.
All accepted papers of ICCSS 2015 will be published
in the one of the following Journal with ISSN.
International Journal of Electronics and Electrical
Engineering(IJEEE)(ISSN: 2301-380X)
ICCSS 2015
2015 5th International
Conference on Circuits, System
and Simulation
http://www.iccss.org/
Indexed by Ulrich's Periodicals Directory, Google
Scholar, EBSCO, Engineering & Technology Digital
Library and Electronic Journals Digital Library.
International Journal of Information and Electronics
Engineering(IJIEE)(ISSN: 2010-3719)
Indexed by Google Scholar, Electronic Journals Library,
Engineering & Technology Digital Library, Crossref and
ProQuest, DOAJ, Ei (INSPEC, IET).
All accepted papers of ICROM 2015 will be published
by Advanced Materials Research (ISSN: 1022-6680)
July20-21
2015
Madrid
Spain
ICROM 2015
ICAME 2015
The 2nd International
Conference on Robotics and
Mechatronics
http://www.icrom.org/
2015 the 4th International
Conference on Advances in
Mechanics Engineering
http://www.icame.org/
Indexed by Elsevier: SCOPUSwww.scopus.com and Ei
Compendex (CPX) www.ei.org/. Cambridge Scientific
Abstracts (CSA) www.csa.com, Chemical Abstracts
(CA) www.cas.org, Google and Google Scholar
google.com,
ISI
(ISTP,
CPCI,
Web
of
Science) www.isinet.com , Institution of Electrical
Engineers (IEE)www.iee.org , etc
All accepted papers of ICAME 2015 will be published
by Advanced Materials Research (ISSN: 1022-6680)
Applied Mechanics and Materials (ISSN: 1660-9336) is
Indexed by Elsevier: SCOPUSwww.scopus.com and Ei
Compendex (CPX) www.ei.org/. Cambridge Scientific
Abstracts (CSA) www.csa.com, Chemical Abstracts
(CA) www.cas.org, Google and Google Scholar
google.com,
ISI
(ISTP,
CPCI,
Web
of
Science) www.isinet.com , Institution of Electrical
Engineers (IEE)www.iee.org , etc
From the next year, those conferences will be organized and
assisted by American Society for Research(ASR), for more
conferences and information about ASR, please visit:
http://www.asr.org/
The 2014 IACSIT Beijing Conferences
Note
The 2014 IACSIT Beijing Conferences