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Teaching Reform and Innovation of the Course - Digital Image processing Experiments

Teaching Reform and Innovation of the Course - Digital Image...

The 5th International Conference on Computer Science & education(第五届国际计算机新技术与教育学术研讨会 ICCSE'10)

作者： Haifeng Zhao Jin Tang Bin Luo Key Lab of Intelligent Computing & Signal Processing of Ministry of Education School of Computer Science and TechnologyAnhui UniversityHefei230039P. R. China

Digital image processing is an interdisciplinary course, which needs students have a strong background in mathematics. To help them change from passive learning to active learning, teaching reform and innovation of the course "Digital Image processing Experiments" is discussed in this paper. The combined platform of experiments includes TI DSP experimental box and three different kinds of programming languages. The six experimental projects cover the basic theories of digital image processing. The result can offer a significant reference for the teaching innovations in the other related specialties.

关键词： digital image processing:experimental teaching matlab:DSP

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Non-rigid object reconstruction based on multi-view images: A survey

Non-rigid object reconstruction based on multi-view images: ...

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2010 3rd International Congress on Image and signal processing, CISP 2010

作者： Liu, Zhi Wang, Hongjun Li, Qingli Jun, Shi School of Information Science and Engineering Shandong University Jinan China Key Laboratory of Intelligent Computing and Information Processing Ministry of Education China School of Information Science East China Normal University Shanghai China Shandong Institute of Light Industry Jinan China

ISBN: (纸本)9781424465149

In this paper we review the major approaches to non-rigid object reconstruction based on multi-view images. It tries to reflect the profile of this area by focusing more on those subjects that have been given more importance in the literature. In this context most of the paper is devoted to present all kinds of approaches for non-rigid object reconstruction based on multi-view images. A number of references are provided that describe applications of non-rigid object reconstruction based on multi-view images The paper ends by addressing some important issues and open questions that can be subject of future research. ©2010 IEEE.

关键词： Image reconstruction

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A Distributed Group Signature Scheme with Traceable Signers for Mobile Ad Hoc Networks

A Distributed Group Signature Scheme with Traceable Signers ...

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The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

作者： Hong Zhong Runhua Shi Key Laboratory of Intelligent Computing & Signal Processing Anhui University Ministry of Education Hefei China 230039 School of Computer Science and Technology Anhui University Hefei China 230039

ISBN: (纸本)9781424472352

In this paper, we propose a distributed group signature scheme with traceable signers for mobile Ad hoc networks. In such scheme, there isn't a trusted center, and all members of Ad hoc group cooperate to generate all system parameters and all private/public keys. Any ' members in Ad hoc group can collaboratively generate the group signature with the help of a designated clerk, where the signer respectively generates the partial signature by using his private key and the clerk can check the correctness of the partial signature. Furthermore, anyone can verify the validity of the group signature by the group public key and trace back to find the identities of signers from the warrant created by the clerk. What's more, it can dynamically increase the parameter values of ~t and ~n, according to the actual security needs of mobile Ad hoc networks, but the private and public keys of the whole Ad hoc group still are not changed for relatively long-term stability.

关键词： group signature shamir's secret sharing mobile ad hoc networks traceable distributed

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Improved particle swarm algorithm for portfolio optimization problem

Improved particle swarm algorithm for portfolio optimization...

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International Conference on Industrial Mechatronics and Automation, ICIMA

作者： Jianguo Cao Liang Tao Department of Computer Science Anhui Vocational and Technical College of Industry and Trade Huainan China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781424476534

Particle swarm optimization (PSO) is a recently proposed population-based random search algorithm, which performs well in some optimization problems. In this paper, we proposed an improved PSO algorithm to solve portfolio selection problems. The proposed approach IPSO employs an opposite mutation operator to enhance the performance of the standard PSO. In order to verify the performance of IPSO, we test it on five well-known benchmark function optimization problems. At last, we use IPSO to solve a classical portfolio selection problem. The results show that the proposed approach is effective and achieves better results than standard PSO.

关键词： Particle swarm optimization Portfolios signal processing algorithms Benchmark testing Artificial neural networks Computer industry educational institutions Genetic mutations Optimization methods Support vector machines

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Predicting RNA secondary structure with Tabu Search

Predicting RNA secondary structure with Tabu Search

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IEEE International Conference on Cognitive Informatics

作者： Liu, Yongguo Hao, Jianrui Peng, Jun School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China Key Laboratory of Intelligent Computing and Information Processing Ministry of Education Xiangtan University Xiangtan 411105 China College of Electronic Information Engineering Chongqing University of Science and Technology Chongqing 400050 China

ISBN: (纸本)9781424480401

In this paper, a novel method for predicting RNA secondary structure called RNA secondary structure prediction based on Tabu Search (RNATS) is proposed. In RNATS, two search models, intensification search and diversification search, are designed to exploit the local regions around the current solution and explore the unvisited space, respectively. Simulation experiments are conducted for six RNA sequences to show that the proposed method is feasible and effective. © 2010 IEEE.

关键词： Tabu search

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Image denoising based on Non-Local means and multi-scale dyadic wavelet transform

Image denoising based on Non-Local means and multi-scale dya...

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International Conference on Computer Science and Information Technology (CSIT)

作者： Gang Yu Yong Yin Hongjun Wang Zhi Liu Dengwang Li School of Information science and engineering Shandong University Lin'an China Key Laboratory of Intelligent Computing & Information Processing Ministry of Education Xiangtan China

A variety of wavelet transform methods have been introduced to remove noise from images. However, many of these algorithms remove the fine details and smooth the structures of the image when removing noise. The wavelet coefficient magnitude sum (WCMS) algorithm can preserve edges, but it is at the expense of removing noise. The Non-Local means algorithm can removing noise effective. But it tend to cause distortion ( eg white). Meanwhile, when the noise is large, the method is not so effective. In this paper, we propose an efficient denoising algorithm. we denoised the image with non-local means algorithm in the spatial domain and WCMS algorithm in wavelet domain, weighted, combined them and got the image that we want. The experiment shows that our algorithm can improve PSNR form 0.6 dB to 1.0 dB and the image boundary is more clearly.

关键词： Discrete wavelet transforms Image edge detection PSNR Histograms Noise reduction

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CBCT image denoising based on multi-scale wavelet transform

CBCT image denoising based on multi-scale wavelet transform

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International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Yong Yin Gang Yu Hongjun Wang Zhi Liu Dengwang Li School of Information science and engineering Shandong University Jinan China Key Laboratory of Intelligent Computing Information Processing of Ministry of Education Xiangtan China

Cone-Beam Computed Tomography (CBCT) has always been in the forefront of medical image processing. The denoising as a image pre-processing, has a great affected on the image analysis and recognition. In this paper, a new algorithm for image denoising was proposed. By thresholding the interscale wavelet coefficient magnitude sum(WCMS) within a cone of influence (COI), the wavelet coefficients are classified into 2 categories: irregular coefficients, and edge-related and regular coefficients. They are processed by different ways. Meanwhile according to the projection image sequences characteristics in CBCT system, an effective noise variance estimated methods was proposed. The experiment shows that our algorithm can improve PSNR form 1.3dB to 2.6dB, and the image border is more clearly.

关键词： Noise Wavelet coefficients Image reconstruction Classification algorithms Noise reduction Image edge detection Image denoising

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Subspace selection using semi-supervised harmonic mean of Kullback-Leibler divergences

Subspace selection using semi-supervised harmonic mean of Ku...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Si-Bao Chen Hai-Xian Wang Bin Luo Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui China Key Lab of Child Development and Learning Science of Ministry of Education Research Center of Learning Sciences South-East University Nanjing Jiangsu China

In many areas of pattern recognition and machine learning, subspace selection is an essential step. Fisher's linear discriminant analysis (LDA) is one of the most well-known linear subspace selection methods. However, LDA suffers from the class separation problem. The projection to a subspace tends to merge close class pairs. A recent result, named maximizing the geometric mean of Kullback-Leibler (KL) divergences of class pairs (MGMD), can significantly reduce the class separation problem. Furthermore, maximizing the harmonic mean of Kullback-Leibler (KL) divergences of class pairs (MHMD) emphasizes smaller divergences more than MGMD, and deals with the class separation problem more effectively. However, in many applications, labeled data are very limited while unlabeled data can be easily obtained. The estimation of divergences of class pairs is unstable using inadequate labeled data. To take advantage of unlabeled data for subspace selection, semi-supervised MHMD (SSMHMD) is proposed using graph Laplacian as normalization. Quasi-Newton method is adopted to solve the optimization problem. Experiments on synthetic data and real image data show the validity of SSMHMD.

关键词： Harmonic analysis Training Laplace equations Manifolds Covariance matrix Machine learning Symmetric matrices

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On Dynamic Weighting of Data in Clustering with K-Alpha Means

On Dynamic Weighting of Data in Clustering with K-Alpha Mean...

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International Conference on Pattern Recognition

作者： Si-Bao Chen Hai-Xian Wang Bin Luo Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui China Key Laboratory of Child Development and Learning Science of Ministry of Education Research Center of Learning Science South-East University Nanjing Jiangsu China

ISBN: (纸本)9781424475421

Although many methods of refining initialization have appeared, the sensitivity of K-Means to initial centers is still an obstacle in applications. In this paper, we investigate a new class of clustering algorithm, K-Alpha Means (KAM), which is insensitive to the initial centers. With K-Harmonic Means as a special case, KAM dynamically weights data points during iteratively updating centers, which deemphasizes data points that are close to centers while emphasizes data points that are not close to any centers. Through replacing minimum operator in K-Means by alpha-mean operator, KAM significantly improves the clustering performances.

关键词： Clustering algorithms Heuristic algorithms Indexes Partitioning algorithms signal processing algorithms Euclidean distance Iris

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Study of high-resolution range profile for monostatic MIMO radar based on SIAR

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Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics 2010年第4期32卷 734-739+763页

作者： Zhao, Guang-Hui Chen, Bai-Xiao Gao, Zhao-Zhao Intelligent Perception and Image Understanding Key Lab of Ministry of Education of China Xidian Univ. Xi'an 710071 China National Key Lab for Radar Signal Processing Xidian Univ. Xi'an 710071 China National Information Control Laboratory Chengdu 610036 China

Conventional pulse compression use a periodical echo of single receive antenna, which is modulated by a certain carrier-frequency, in other words, single spectrum is exploited. But for MIMO radar, as the multi-carrier-frequency signals are transmitted simultaneously, if the spectrum of the target echo after channel separation can be combined to form the whole band spectrum echo, the corresponding range resolution can improve several times as compared with the conventional method, and it will be more convenient for follow-up detection and tracking. Considering the difference between the frequency modulation band and the interval between the adjacent frequencies, the spectrum joint after channel separation will be overlapped or spaced. The methods of spectrum moving of each echo and the spectrum extrapolation with Root-MUSIC algorithm are proposed, by which high-resolution range profile of the target is obtained. Simulation results verify the validity of these methods.

关键词： Multiple signal classification

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