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International Conference on Computer Modeling and Simulation, ICCMS

作者： Hong Liu Yu Jia Hong Cheng Sui Wei Education Ministry Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China

According to defocus imaging theory, the amount of blur in the defocus images varies with depth of the object in the scene. So depth in the scene can be recovered by estimating the blur with the knowledge of the lens parameters. A novel application of the total variation principle is made for the estimation of the amount of blur in the defocus images. Three main processes are included: the process of image defocusing is modeled using the model of anisotropic heat diffusion, then the depth recovery problem is translated into the minimum problem of energy functional with total variation regularization, and the gradient flow is used to seek the optimal solution. The recovery of focus image and the excess restrictions are avoided. The experiment results show that the algorithm is quite effective and depth information in edge is well retained particularly. Compared with the least square algorithm, depth recovery error with the total variation algorithm is reduced about 40%.

关键词： Layout Lenses Focusing signal processing algorithms Least squares approximation Anisotropic magnetoresistance Heat recovery Polynomials Robot vision systems Cameras

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Manifold feature extraction for video based on locally linear embedding

Manifold feature extraction for video based on locally linea...

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International Conference on Computer Science and education

作者： Fu, Maosheng Xu, Qin Kong, Min Luo, Bin Key Lab. of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China Department of Computer Science and Technology West Anhui University Anhui Lu'an 237012 China

ISBN: (纸本)9781424460052

Locally linear embedding (LLE) is an elegant nonlinear method for feature extraction and manifold learning, which attempt to project the original data into a lower dimensional feature space by preserving the local neighborhood structure. However, LLE algorithm fails when it is directly applied to video with multi-shot. In this paper, video manifold feature is defined firstly, and then using LLE we extract video manifold feature through adding virtual frames on an enriched set. The proposed manifold feature extraction method is applied to shot transition and video trajectories. The video manifold feature description gives a new tool for video analysis. ©2010 IEEE.

关键词： Feature extraction

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2010 IEEE 5th International Conference on Bio-Inspired computing: Theories and Applications, BIC-TA 2010

作者： Zhang, Zhujin Wang, Shuo Zhang, Xingyi Zhang, Zheng Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China School of Computer and Information Science University of South Australia Adelaide SA 5095 Australia Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei 230039 China

ISBN: (纸本)9781424464388

Randí et al. proposed a significant graphical representation for DNA sequences, which is very compact and avoids loss of information. In this paper, we build a fast algorithm for this graphical representation with time complexity O(n2), and find another important advantage in the representation: no degeneracy. Moreover, we propose a new method to do similarity analysis of DNA sequences based on the representation. The approach adopts four elements of covariance matrix as a descriptor, and is illustrated on the first exon of beta-globin genes from 11 different species. © 2010 IEEE.

关键词： DNA sequences

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Speech Endpoint Detection in Noisy Environments Using EMD and Teager Energy Operator

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Journal of Electronic Science and Technology 2010年第2期8卷 183-186页

作者： De-Xiang Zhang Xiao-Pei Wu Zhao Lv Key Lab. of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China

Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition （EMD） algorithm and Teager energy operator （TEO） is proposed to locate endpoint intervals of a speech signal embedded in noise. With the EMD, the noise signals can be decomposed into different numbers of sub-signals called intrinsic mode functions （IMFs）, which is a zero-mean AM-FM component. Then TEO can be used to extract the desired feature of the modulation energy for IMF components. In order to show the effectiveness of the proposed method, examples are presented to show that the new measure is more effective than traditional measures. The present experimental results show that the measure can be used to improve the performance of endpoint detection algorithms and the accuracy of this algorithm is quite satisfactory and acceptable.

关键词： Index Terms----Empirical mode decomposition endpoint detection noisy speech Teager energy operator.

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Locating Human Eyes in Face Images Based on Illumination Normalization and Progressive Thresholding

Locating Human Eyes in Face Images Based on Illumination Nor...

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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： Hua-bin Wang Liang Tao Xue-you Hu Shi-yi Wang Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University HefeiAnhui230039China

Based on illumination normalization and progressive thresholding, this paper presents a novel algorithm for automatic localization of human eyes in still images with complex background. First of all, Retinex method is used to realize normalizing of the face image. Secondly, a determination criterion of eye location is established by the priori knowledge of geometrical facial features. Thirdly, a range of threshold values that would separate eye blocks from others in a segmented face image is estimated. With the progressive increase of the threshold by an appropriate step in that range, once two eye blocks appear from the segmented image, they will be detected by the determination criterion of eye location. Finally, the 2-D correlation coefficient is used as a symmetry similarity measure to check the factuality of the two detected eyes. The experimental results demonstrate the high efficiency of the algorithm in runtime and correct localization rate.

关键词： detecting and locating human eyes:image segmentation:skin color segmentation:face recognition

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Mobility robustness optimization based on UE mobility for LTE system

Mobility robustness optimization based on UE mobility for LT...

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International Conference on Wireless Communications and signal processing (WCSP)

作者： Zhenzhen Wei Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University of Science and Technology Hefei China

Self-organizing networks (SON) for cellular systems are emerging as an important technology to reduce the cost of network deployment and maintenances. Mobility robustness optimization (MRO) is one of the main use cases of SON and has been intensively studied in 3GPP working groups. In this paper, we take the user equipment (UE) speed into account to solve the MRO problem. We propose a US-MRO algorithm, which assigns different Hysteresis parameters to UEs with different speed. The simulation results show that the success rate of Handover (HO) is improved and user experience is enhanced by the US-MRO algorithm.

关键词： Algorithm design and analysis Optimization Hysteresis Wireless communication Analytical models Robustness Simulation

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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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2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010

作者： Chen, Si-Bao Wang, Hai-Xian Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui 230039 China Key Lab of Child Development and Learning Science of Ministry of Education Research Center for Learning Science Southeast University Nanjing Jiangsu 210096 China

ISBN: (纸本)9781424459346

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. ©2010 IEEE.

关键词： Discriminant analysis

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SPEECH ENDPOINT DETECTION IN NOISY ENVIRONMENTS USING EMD AND TEAGER ENERGY OPERATOR

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Journal of Electronic Science and Technology 2010年第2期000卷 183-186页

作者： DE-XIANG ZHANG XIAO-PEI WU ZHAO Lü Key Lab.of Intelligent Computing and Signal Processing of Ministry of Education.Anhui University Hefei 230039China

Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition (EMD) algorithm and Teager energy operator (TEO) is proposed to locate endpoint intervals of a speech signal embedded in noise. With the EMD, the noise signals can be decomposed into different numbers of sub-signals called intrinsic mode functions (IMFs), which is a zero-mean AM-FM component. Then TEO can be used to extract the desired feature of the modulation energy for IMF components. In order to show the effectiveness of the proposed method, examples are presented to show that the new measure is more effective than traditional measures. The present experimental results show that the measure can be used to improve the performance of endpoint detection algorithms and the accuracy of this algorithm is quite satisfactory and acceptable.

关键词： Empirical mode decomposition endpoint detection noisy speech Teager energy operator

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Two protocols for computing the sub-polygon's areas divided by a line

Two protocols for computing the sub-polygon's areas divided ...

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International Conference on Advanced Computer Theory and Engineering, ICACTE

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

Secure Multi-party Computation (SMC) plays an important role in information security under the circumstance of cooperation calculation, so SMC on privacy-preservation is of great interest. In this paper we discuss an issue which is a special SMC problem. Based on Scalar Product Protocol, Monte Carlo Method and Oblivious Transfer, we give two solutions to the problem about how to decide the areas. That is, a polygon is divided into two parts by a line: S 1 and S 2 . Furthermore, we analyze the security and computational complexity, as well as the comparison of these two protocols. The results of analysis show that the proposed protocols are secure and efficient. We believe the two protocols will be useful in other geometric and combinatorial problems.

关键词： Computers Geometry

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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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2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010

作者： Yu, Gang Yin, Yong Wang, Hongjun Liu, Zhi Li, Oengwang School of Information Science and Engineering Shandong University Jinan China Department of Radiation Oncology Shandong Tumor Hospital China Key Laboratory of Intelligent Computing and Information Processing Ministry of Education Xiangtan China

ISBN: (纸本)9781424455386

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, weithted, combined them and got the image that we want. The experiment shows that our algorithm can improve PSNR form 0.6dB to 1.0dB and the image boundary is more clearly. © 2010 IEEE.

关键词： Wavelet transforms

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