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International Journal of Digital Content technology and its Applications 2011年第9期5卷 352-360页

作者： Cheng, Zheng Xiaodong, Zhu Jingcheng, Li Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education Anhui University China School of Computer Science and Technology Anhui University China Institute of Information Management and Electronic Business University of Shanghai for Science and Technology China

How to make use of limited memory space and processing speeds of computer for rapid and accurate data mining has become an important research topic on the stream data cluster analysis. A stream data clustering algorithm based on the minimum spanning tree (MSTSC) is described. MSTSC is divided into online processing and offline clustering. Stream data are analyzed online by using two groups of processing unit respectively. In offline process clusters is taken as representative objects, and the minimum spanning tree algorithm is used in offline clustering. MSTSC can improve the clustering quality on non-spherical clusters. Some experiments are carried out in both real data sets and synthetic data sets. Results show that MSTSC algorithm not only can deal with non-spherical clusters effectively, but also has better efficiency and clustering quality. In addition, MSTSC is insensitive to order of input data, and has a good effect for skewed class distributions.

关键词： Cluster analysis

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Multi-kernel Co-SVM with a new strategy using unlabeled data for image retrieval

Multi-kernel Co-SVM with a new strategy using unlabeled data...

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International Conference on Pervasive Computing and Applications (ICPCA)

作者： Li Zongmin Liu Yang Li Hua School of Computer and Communications Engineering China University of Petroleum Shandong China Key Laboratory Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781457702099

Relevance feedback based on SVM classifier shows a good performance recently but the finite feedback counts limited by user's patience and the small sample size problem are not solved well, Co-SVM does a good job in solving these problems but still has some flaws. We propose three strategies to try to improve this algorithm: (1) different kernel functions are used to characterize the color and texture visual similarities; (2) a new method is proposed to caculate the confident scores of the contention samples; (3) a bunch of the most irrelevant images with the highest confident score are added into the labeled images to extend the size of labeled data while choosing a bunch of images for user labeling. Experimental results verify the superiority of our method over Co-SVM.

关键词： Support vector machines Multimedia communication Classification algorithms

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A novel coarse-to-fine hair segmentation method

A novel coarse-to-fine hair segmentation method

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International Conference on Automatic Face and Gesture Recognition

作者： Dan Wang Xiujuan Chai Hongming Zhang Hong Chang Wei Zeng Shiguang Shan Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China NEC Laboratories Beijing China

Segmenting hair regions from human images facilitates many tasks like hair synthesis and hair style trends forecast. However, hair segmentation is quite challenging due to hair/background confusion and large hair pattern diversity. To address these problems to some extent, this paper proposes a novel coarse-to-fine hair segmentation method. In our approach, firstly, the recently proposed “Active Segmentation with Fixation” (ASF) is used to coarsely define an enclosed candidate region with high-recall (but possibly low-precision) of hair pixels and exclude considerable part of the backgrounds which are easily confused with hair. Then Graph Cuts (GC) method is applied to the candidate regions to remove additional false positives by incorporating hair-specific information. Specifically, Bayesian method is employed to select some reliable hair and background regions (seeds) among the ones over-segmented by Mean Shift. SVM classifier is then learnt online from these seeds and explored to predict hair/background likelihood probability, which is subsequently fed into GC algorithm. The novelty of the proposed approach lies in three folds: 1) an elaborate design of hair segmentation framework, which utilizes ASF to reduce the candidate hair regions and adopts GC to achieve more accurate hair region contours; 2) the region-based strategy for seed selection; 3) the exploration of the discriminative method, SVM, to predict the probability of each pixel belonging to hair and background regions. Extensive experimental results demonstrate the approach outperforms recently proposed methods.

关键词： Hair Pixel Image segmentation Support vector machines Bayesian methods Image color analysis Databases

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Estimating the Connection Probability for 2-D Mesh Networks by Monte Carlo Methods

Estimating the Connection Probability for 2-D Mesh Networks ...

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International Conference on Computer and Management (CAMAN)

作者： Meilian Liang Binmei Liang Zehui Shao Xiaodong Xu School of Mathematics and Information Science Guangxi University Nanning China Key Laboratory of Pattern Recognition and Intelligent Information Processing School of Information Science & Technology University of Chengdu Chengdu China Guangxi Academy of Sciences Nanning China

Fault tolerance is a central issue in the design and implementation of interconnection networks for large parallel systems. Connection probability of a network is a good network fault tolerance measure. For a mesh of given size and node failure probability, the gap between the known upper and lower bounds on the connection probability is often very large. In this paper we design algorithms to estimate the connection probability for 2-D meshes by Monte Carlo methods. The experiment is carefully designed and performed, and the simulation results give good estimates of the connection probability for 2-D meshes and can be used to evaluate the known lower and upper bounds on connection probability for 2-D meshes.

关键词： Mesh networks Fault tolerance Fault tolerant systems Upper bound Monte Carlo methods Computers Simulation

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A Research of Heart Rate Prediction Model Based on Evolutionary Neural Network

A Research of Heart Rate Prediction Model Based on Evolution...

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International Conference on intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Feng Xiao Ming Yuchi Mingyue Ding Jun Jo Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Life College of Science and Technology Huazhong University of Science and Technology Wuhan China School of Information and Communication Technology Griffith University QLD Australia

Heart rate (HR) signal analysis is widely used in the medicine and medical research area. Physical activities (PA) are commonly recognized to greatly affect the changes of heart rate. A method of Evolutionary Neural Network - Neuro-evolution of Augmenting Topologies (NEAT) is used to build a PA-based HR predictor model. Through special coding, crossover and mutation operator, NEAT can implement network topology and connectivity weights evolution simultaneously. The common problem in evolutionary neural network, like competing conventions, how to protect the new innovation are effectively solved. The experimental results demonstrated the application potential of the approach.

关键词： Heart rate Biological neural networks Training Monitoring Neurons Encoding Biomedical monitoring

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Image retrieval based on color features integrated with anisotropic directionality

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Journal of Systems Engineering and Electronics 2010年第1期21卷 127-133页

作者： Jing Bai Xiaohua Wang Licheng Jiao Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 P. R. China

A novel image retrieval approach based on color features and anisotropic directional information is proposed for content based image retrieval systems （CBIR）. The color feature is described by the color histogram （CH）, which is translation and rotation invariant. However, the CH does not contain spatial information which is very important for the image retrieval. To overcome this shortcoming, the subband energy of the lifting directionlet transform （L-DT） is proposed to describe the directional information, in which L-DT is characterized by multi-direction and anisotropic basis functions compared with the wavelet transform. A global similarity measure is designed to implement the fusion of both color feature and anisotropic directionality for the retrieval process. The retrieval experiments using a set of COREL images demonstrate that the higher query precision and better visual effect can be achieved.

关键词： image retrieval color histogram directionlet transform anisotropic similarity.

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Margin Emphasized Metric Learning and its application to Gabor feature based face recognition

Margin Emphasized Metric Learning and its application to Gab...

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International Conference on Automatic Face and Gesture Recognition

作者： Shaoxin Li Shiguang Shan Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computer Technology Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN

In addressing side information based face recognition scenario, a new Margin Emphasized Metric Learning (MEML) method is proposed. As an improvement of previous metric learning, MEML defines a new objective function for optimization, which adds more weights to sample pairs on the boundary thus hard to classify. To further improve face verification performance, MEML is applied to Gabor feature in a block dividing and combining mode. Experiments on LFW image-restricted setting illustrate very impressive performance compared with traditional methods. By combining multiple MEML classifiers on several features, performance comparable to the best known results on LFW is achieved.

关键词： Measurement Face Face recognition Accuracy Training Databases Robustness

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Quantitative Study on Despeckle Methods of Medical Ultrasound Images

Quantitative Study on Despeckle Methods of Medical Ultrasoun...

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International Conference on intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Runxia Ma Xuming Zhang Mingyue Ding Qi Liu Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Life College of Science and Technology Huazhong University of Science and Technology Wuhan China School of Electrical Information Engineering Sichuan University Chengdu China

Speckle is a granular noise that inherently exists in all types of coherent imaging systems. This paper presents a quantitative study on five despeckling methods such as frost filter, kuan filter, speckle reducing an isotropic diffusion, homomorphic filter and wavelet filter. We select six objective evaluation parameters, such as signal-to-ratio, contrast signal-to-noise ratio, figure of merit, least absolute error, edge protection factor, signal-to-minimum mean square error ratio, to quantify the performance of these filters. The comparative study will provide some parameter comparative reference for selecting a suitable filter in the ultrasound image processing.

关键词： Nonlinear filters Maximum likelihood detection Ultrasonic imaging Noise Speckle Gabor filters Digital filters

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Attention driven face recognition: A combination of spatial variant fixations and glance

Attention driven face recognition: A combination of spatial ...

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International Conference on Automatic Face and Gesture Recognition

作者： Chongxiu Wang Laiyun Qing Jun Miao Fang Fang Xilin Chen University of the Chinese Academy of Sciences Beijing Beijing CN Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China School of Computer Science and Technology Harbin Institute of Technology Harbin China

This paper proposes a novel face recognition algorithm inspired by the selective attention of Human Visual System (HVS). We record four observers' eye movements when they are viewing 100 FRGC [1] frontal view face images and find that the observers are highly consistent in the regions fixated. Inspired by the fact that fovea of HVS has a much higher spatial acuity than the periphery, a face recognition algorithm based on spatial variant sampling is proposed to simulate such foveated imaging phenomenon, where more information is reserved for the fixated regions. Moreover, information extracted from glance which adopts the low spatial frequency components of the image is integrated into the face recognition system to elicit a percept that occurs before any fixations. The experimental results on FERET database [2] demonstrate that the proposed method not only reduces the computational cost, but also achieves comparable performance, which shows that the characteristics of the HVS provide valuable insights into face recognition.

关键词： Face Face recognition Observers Humans Pixel Databases Feature extraction

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Ultrasound Image Denoising with Multi-shape Patches Aggregation Based Non-local Means

Ultrasound Image Denoising with Multi-shape Patches Aggregat...

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International Conference on intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Wanjun Chen Mingyue Ding Yalin Miao Lei Luo Department of Information Science Xi'an University of Technology Xi'an Shaanxi China College of Life Science and Technology lmage processing and Intelligent Control key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei China

The Non-Local Means (NLM) filter uses the redundancy of information in the image to remove noise, this scheme gives some of the best results among other powerful methods such as wavelet based approaches or diffusion techniques. Though simple to implement and efficient in practice, the classical NLM suffers from ringing artifacts around edges when using square patches, due to an abrupt lack of redundancy of the image. This paper presents an extended NLM based on Multi-Shape Patches Aggregation (NLM-MSPA) to overcome this problem, and uses it to remove medical ultrasound images corrupted by multiplicative speckle noise. We have incorporated a preprocessing step to make the speckle noise much closer to the real additive white Gaussian noise, hence more amenable to a denoising algorithm such as NLM-MSPA. Results on real images and artificially speckled images show that the proposed scheme outperforms several classical methods chosen for comparison in its ability to reduce speckle and preserve edge details.

关键词： Speckle Ultrasonic imaging Noise reduction Shape Biomedical imaging Signal to noise ratio

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