Conference Program of WCICA 2012

WCICA 2012
Book of Abstracts: Saturday Sessions
Yang, Qiong
Beijing Univ. of Tech.
Based on the sensitive character of light sensor, the paper applied the
median filtering algorithm which was used for two-dimensional image
process on the filtering of one-dimensional sensor signal and improved
the algorithm with adding a determine step about heavy interference
signal. The research showed that the miss-rate and the false-rate of
improved median filtering algorithm are 0 and the deviate-rate decent
to 0.2% from 5.1% in classic median filtering algorithm. Therefore,
the improved median filtering algorithm can not only contain the advantages
of classic median filtering algorithm, but also filter the heavy
interference signal efficiently. The algorithm was better in eliminating
the noise and keeping the real signal.
◁ PSaC-69
The Anti-interference analysis and design for Mode S reply Communication
of Integrated TCAS, pp.4467–4471
Huang, Yi
Shi, ZhongKe
Northwestern Polytechnical Univ.
Northwestern Polytechnical Univ.
Abstract―In order to effectively improve the reliability of Mode S reply
communication of integrated TCAS, the anti-interference analysis and
design for the communication circuit and receiving process are provided
in this paper. The algorithms of preamble detection, DF-authentication,
confidence detection of bit are realized by state machines and counters
which were written with VHDL to improve the fault-tolerance. Antiinterference
analysis and design for filter, modulator, demodulator, amplifier
and detector is also provided to improve the reliability of communication.
Finally, the anti-interference design is tested by wireless
communication experiment. The result indicates that the algorithms
which realized with FPGA can detect and decode Model S reply signal
accurately with a certain fault-tolerant ability; the rise/fall time of pulse
is less then 50ns, the jitter amplitude of signal is less than 3dB which
agrees with RTCA standards for Model S reply communication.
◁ PSaC-70
Remarks on Outliers in Time Series of Stock Prices Based on Density,
pp.4523–4526
ZHAO, Qingjiang
Kunming Univ.
How to detect the outlier of stock prices effectively has become an intense
concern of scholars in many fields. In this paper, the thoughts
of Statistical theory and local density are introduced for researching the
outliers in stock time series. A method detecting the outlier of stock time
series based on density is proposed. Study on the outlier of time series
in stock market is dealt with in two stages. In the first stage, the time
series is partitioned by means of the sliding window with fixed length.
In the second stage, the density-based method is introduced to detect
the outliers with the local outlier factor. Empirical study, based on the
daily closing price of SSE Composite Index, proved that the method is
feasible and effective.
◁ PSaC-71
Support Vector Machine Based Aircraft Ground Icing Type Classification
Forecast, pp.4541–4544
Xing, Zhiwei
Zhang, Hui
Civil Aviation Univ. of China
Civil Aviation Univ. Of China
Aircraft icing can seriously affect the safety of aircraft, and different
types of aircraft icing have an effect on the aircraft safety to various
extents. A SVM (Support Vector Machine) model for aircraft icing type
prediction is presented to classify aircraft icing types. The input variables
of icing type are analyzed, and then based on the analysis, the
appropriate forecast methods are chosen and a SVM model for aircraft
icing type classification is established. The SVM-based classification
model is employed to identify aircraft ground icing type and compare
with the classification model based on BP neural network. The experimental
results show that the model based on the SVM method supplies
high forecast accuracy, strong generalization ability with small samples,
and has broad application prospect.
◁ PSaC-72
Fusion Algorithm of Infrared and Visible Images Based on Local Energy
Using NSCT, pp.4579–4582
DAI, Wen-zhan
TAN, Libo
Yang, Aiping
zhejiang Sci-Tech Univ.
Inst. of Automatic Control, Zhejiang Sci-Tech Univ.
Zhejiang Univ. of Finance & Economics
According to the characteristics of the infrared and visible image, an
image fusion algorithm of infrared and visible images based on local
average energy using NSCT is proposed. After the two original images
-registered are decomposed by using NSCT, the low frequency
sub-band coefficients and band-pass directional sub-band coefficients
are given by fusion rules based on local average energy, and then the
fused image is obtained by inverse NSCT .The simulation results show
that the algorithm proposed in this paper is best among wavelet-based,
Curvelet-based and NSCT-based method.
◁ PSaC-73
Fingerprint Orientation Reconstruction from Minutiae Points, pp.4583–
4587
Chu, Zhuang
Yuan, Guosen
Zhang, Xiyu
Han, Lin
Henan Mechanical & Electrical Engineering
College
Henan Mechanical & Electrical Engineering
College
CNNC CHINA NUCLEAR POWER ENGINEERING
Co
Xin Xiang Medical Univ.
Fingerprint orientation reconstruction from minutiae points is an important
procedure in fingerprint reconstruction. In this paper, a novel
fingerprint orientation reconstruction method is proposed. Firstly, the
initial orientation field is estimated through interpolation strategy. The
orientation of central block is predicted by the nearest minutia in eight
different sectors. Secondly, a 2-D Fourier series expansion method for
orientation field is proposed. Using the coefficients of expansion function,
orientation field can be presented and reconstructed effectively.
The noise can also be eliminated evidently through this method. Furthermore,
singular points which are always needed for other orientation
model are not required by 2-D Fourier series expansion method. The
experimental results comparing our method with other methods prove
that our proposed method is very effective in representing and reconstructing
the fingerprint orientation field.
◁ PSaC-74
Image fusion via wavelet transform based on local contrast, pp.4588–
4591
Zhang, Daosong
Pan, Haipeng
Zhejiang Sci-Tech Univ.
Zhejiang Sci-Tech Univ.
In this article, images obtained by multi-sensor use multi-resolution
analysis of image fusion methods based on wavelet transform. Two
source images obtained high frequency and low frequency components
after wavelet transform. Using fusion rules with criteria based on local
variance [7] to obtain low-frequency component. using an adaptive algorithm
with local contrast of images to obtain the high-frequency component;
at last, using inverse wavelet transform to rebuild a fusion image
with useful information from source image. Results show that compared
with traditional algorithm and general algorithm, fusion image
obtained by the proposed algorithm increases Peak-to-peak Signal-to-
Noise Ratio by 12.11% and 8%, reduces root mean square error by
69.65% and 59.80%, increases correlation coefficient by 0.95% and
0.52%.
◁ PSaC-75
An Algorithm for Human Eye Location in Complex Background Based
on Image Processing, pp.4592–4595
Wu, Minjie
Mu, Ping’an
Dai, Shuguang
Zhang, Cai-Yan
Univ. of Shanghai for Sci. & Tech.
College of Optical & Electronics Engineering
Univ. of Shanghai for Sci. & Tech.
Univ. of Shanghai for Sci. & Tech.
In order to reduce the impact of image background and illumination in
face locating, this dissertation has put forward a new algorithm to locate
human eyes, applying YCbCr model to extract human face region, and
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