Conference Program of WCICA 2012

Conference Program WCICA 2012
discussed. And then, the wavelet transform is used to process echo
signals, the low-frequency energy and the high-frequency energy are
extracted as characteristics of echo signal in time-frequency domain.
At last, a fuzzy pattern recognition algorithm is designed to evaluate the
bonding quality of the composite material, it is based on the maximum
membership degree principle. Simulation proved that the algorithm can
recognize different echo signals quantitatively and effectively.
◁ PSaC-03
A Fast Stereo Matching Algorithm Used in Target Recognition of Mobile
Robot, pp.4771–4774
Yu, Naigong
Lin, Jia
Huang, Can
Ruan, Xiaogang
Beijing Univ. of Tech.
Beijing Univ. of Tech.
Beijing Univ. of Tech.
Beijing Univ. of Techbnology
For the accuracy and real-time requirements of stereo matching when
mobile robot recognizes the target, an improved winner-take-all (WTA)
algorithm which is based on the parallel binocular system is proposed.
First, extract the relatively big difference points between two images
as feature points. Then, implement the stereo matching for the feature
points using WTA algorithm and only implement a simple verification
for nonfeature points. Nonfeature points’disparity values are
the ones of neighboring pixel. Finally, obtain a dense disparity map.
The extracted feature points focus on the disparity discontinuity regions
and the matching accuracy of the algorithm is equivalent to other existing
algorithms.But calculation speed of the algorithm is faster and its
edge feature is better.So it is a stereo matching algorithm with accurate
matching and good real-time.
◁ PSaC-04
Smelting Process Smoke Detection using Multivariate Image Analysis,
pp.4865–4868
Zhang, Hongwei
Song, Zhihuan
Zhejiang Univ.
Zhejiang Univ.
To solve the problems that available technology was difficult to detect
smoke concentration in the smelting process, this paper presented
investigations into the smoke detection using multivariate image analysis.
Firstly, smoke image matrix was transformed to a new one with
single row and high dimension columns. Then the transformed matrix
was processed by principal components analysis (PCA) to extract principal
components (PCs). Finally, smoke concentration was detected by
the two extracted PCs and threshold values. The correlations between
PCs and smoke concentration were also identified and analyzed. The
results of industrial application show that the proposed method could
detect the smoke concentration effectively.
◁ PSaC-05
Optical Flow Estimation with Parameterized Data Term and Warping,
pp.4633–4637
Xu, Jintao
Feng, Zuren
Lu, Na
Xi’an Jiaotong Univ.
Xi’an Jiaotong Univ.
Xi’an Jiaotong Univ.
Horn/Schunck approach which has been widely used in variational optical
flow estimation consists of a data term and a smoothness term.
In this paper, a parameterized data term is proposed. The parameter
can adjust the proportion of the two images’gradient for obtaining
the Euler-Lagrange equations. This combination makes the optical flow
more robust to noise and illumination changes. Firstly, the classic model
is analyzed, especially the coefficients of the Euler-Lagrange equations.
Then, a model with parameterized data term is proposed. This
model has formulated the combination of image gradients theoretically
and enabled more flexible combination. Finally, a multi-resolution technology
has been used for solving the nonlinearity of optical flow. In this
process, the warping step is also parameterized and the influence of
the parameter is analyzed. The experiments demonstrate the benefit of
our parameterized model to the classical one.
◁ PSaC-06
Hardware Design of The Wireless Automatic Meter Reading System
Based on GPRS, pp.4536–4540
Zhang, Ying
Univ. of Anshan
With the rapid development of computer network and electronic information
technology, automatic and intelligent electronic products play
roles that can not replaced by people themselves. Reading technology
is a new technology that is applied in remote automatic data collection,
transmission and processing for water, electricity, gas supply and management
system, etc.. Hardware of wireless communication system
based on GPRS was designed for remote automatic meter reading in
this paper. The module supports UDP communication protocols, and
can transmit remote data by the methods of messaging and network
communications.
◁ PSaC-07
ANALYSIS OF MULTI-BIOMETRIC ENCRYPTION AT FEA-TURE-
LEVEL FUSION, pp.4563–4567
Fu, Bo
Univ. of Electronic Sci. & Tech. of China
The basic concepts and methods on performance and effectiveness
evaluations at the feature-level fusion model of multi-biometric encryption
are concentrated on in this paper. From the cryptographic theory
point of view, firstly, the formal definitions related to mul-ti-biometric
cryptosystems are formulated. Under some extreme conditions, the security
and privacy of mul-ti-biometric cryptosystems at the feature level
are ana-lyzed and rigorously proved. Finally, a close relationship between
security and privacy and the fundamental tradeoff between the
accuracy and security are studied.
◁ PSaC-08
Classification Network of Gastric Cancer Construction based on Genetic
Algorithms and Bayesian Network, pp.4676–4681
He, Yiheng
BeiJing Univ. of Tech.
One of the most important link in improves diagnostic accuracy and
disease cure rate is accurate classification of disease.The current gene
chip’s development and widely applications making the diagnosis based
on tumor gene expression profiling expectedto be on a fast and effective
clinical diagnostic method. But the sample of gene is small and
the expression data is multi-variable. In this article, we uses three data
sets on gene expression profiles of gastric cancer for the construction
of classification model, First, screened the gene which significantly
changed in expression pattern, and use these genes as a set of the
feature to reduce the number of variables, and then using genetic algorithms
and bayesian network model to build the classifier, the build
process uses these three gene expression data to learn classifier. Classification
accuracy is calculated by leave-one cross-validation (LOOCV)
and it reached 99.8%. Last we use the GO and pathway to analysis the
classifier’s network structure.
◁ PSaC-09
Distributional Clustering Using Nonnegative Matrix Factorization,
pp.4705–4711
Zhu, Zhenfeng
Ye, Yangdong
Zhengzhou Univ.
Zhengzhou Univ.
In this paper, we propose an iterative distributional clustering algorithm
based on non-negative matrix factorization (DCMF). When factorizing a
data matrix A into CXM, an objective function is defined to impose the
conditional distribution constraints on the base matrix C and the coefficient
matrix M. It has been observed that, in many applications, the
conditional distributions of instances are often employed to normalize
the data dimensions. Taking these factors into account, we simplify the
existent updating rules and obtain the iterative algorithm DCMF. This algorithm
satisfies the constraints described above on condition that the
instance matrix is preprocessed as a conditional distribution. DCMF
is simple, effective, and only needs to initialize the coefficient matrix.
As a result, the base matrix can be viewed as a centroid matrix and
the coefficient matrix just records the membership of fuzzy clustering.
Compared with several other factorization algorithms, the experimental
results on text, gene, and image data demonstrate that DCMF achieves
8.06% clustering accuracy improvement, 35.08% computational time
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