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2011 IEEE Visual Communications and Image processing, VCIP 2011

作者： Shi, Ran Liu, Zhi Xue, Yinzhu Zhang, Xiang School of Communication and Information Engineering Shanghai University Shanghai 200072 China Key Laboratory of Advanced Display and System Application Shanghai University Ministry of Education Shanghai 200072 China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200240 China

ISBN: (纸本)9781457713200

Interactive object segmentation is widely used for extracting any user-interested objects from natural images. A common problem with many interactive segmentation approaches is that the object segmentation quality is degraded due to inaccurate object/background seeds provided by the user. This paper proposes an iterative adjustable graph cut to efficiently solve this problem. First, object/background seeds are initialized based on the object segmentation result obtained with the user-specified scribbles as the interactive input. Then, an iterative seed adjustment scheme is exploited to correct inaccurate seeds and extract new suitable seeds via graph cut, in which the balancing weight between energy terms are adaptively updated to protect stable seeds and speedup the iteration process. Finally, suitable seeds are obtained and graph cut is used to segment the objects. Experimental results demonstrate the better segmentation performance of our approach even if user provides rather rough seeds. © 2011 IEEE.

关键词： Image segmentation

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Image enhancement based on improved fractional differentiation

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Journal of Computational information Systems 2011年第1期7卷 257-264页

作者： Gao, Chaobang Zhou, Jiliu Zheng, Xiuqing Lang, Fangnian College of Information Science and Technology Chengdu University Chengdu 610106 China Key Laboratory of Pattern Recognition and Intelligent Information Processing Sichuan Province Chengdu 610106 China School of Computer Science Sichuan University Chengdu 610064 China

In this paper, according to the development of the fractional differentiation and its applications in the modern signal processing, we improve the numerical calculation of fractional differentiation by piecewise quadratic interpolation equation, that is, improved fractional differentiation, IFD for short, and propose a new corresponding operator, IFD operator. And we apply this new operator to image enhancement. Experiments show that, for texture-rich digital image, the capability of nonlinearly enhancing comprehensive texture details by IFD is very obvious. For quantity analysis, we particularly calculate the information entropy and average gradient. Comparing with fractional differentiation, the image obtained by IFD is clearer. © 2011 Binary information Press.

关键词： Image enhancement

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Threshold selection using partial structural similarity

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2011年第7期5卷 397-407页

作者： Lu, Haifeng Zhang, Tianxu Yan, Luxin State Key Laboratory for Multi spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

A novel image threshold selection approach based on structural similarity (SSIM) is proposed. The thresholded image is obtained first, then comparison regions are extracted based on the local variance of the neighborhood of the thresholded image. Due to the characteristic of comparison regions, the conventional SSIM expression is simplified as a nonparametric form, and the partial SSIM (PSSIM) is defined. The optimal threshold is selected by maximizing the PSSIM criterion function at last. Besides the introduction of a novel approach, this is also the first attempt to expand the application scope of SSIM to range image thresholding in general. The proposed approach has an advantage over thresholding methods based on the histogram. The method was tested on a variety of images including the synthetic image and real images. Experimental results show that the proposed approach achieves better applicability, preferable ability for extracting object and better anti-noise capability than popular methods.

关键词： Image segmentation

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A new circle targets extraction method from high resolution remote sensing imagery

A new circle targets extraction method from high resolution ...

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Z. Chen J. G. Liu G. Y. Wang Intelligence Control Institute for Pattern Recognition and Artificial Intelligence and Multi-Spectral Information Processing State Key Laboratory Huazhong University of Science and Technology China Intelligence Control Institute for Pattern Recognition and Artificial Intelligence and Multi-Spectral Information Processing State Key Laboratory Huazhong University of Science and Technology China

According to the drawback of the traditional circle target extraction algorithm from high resolution remote sensing imagery used by Hough Transform, such as computation complexity, low efficiency and etc, a new circle target extraction method is proposed in this paper which can extract multiple circle targets with different radius at one time. First, the Average Absolute Difference is implemented to enhance the edge of the circle targets and suppress the noise of the background. Secondly, the locally self-adaptive segmentation algorithm is implemented to obtain the binary image. Thirdly, the thinning algorithm based on model computation is implanted to obtain the single pixel edge of the circle targets and in order to reduce the computation times in the following process. Furthermore, a pruning algorithm is necessary; finally, a modified Hough transform algorithm is proposed to obtain the circle targets. The experimental results demonstrate that the new circle targets algorithm can extract the multiple circle targets quickly and accurately, which has three advantages: low time consuming, high detection rate, robust to noise and fragmentary boundaries.

关键词： Transforms Image edge detection Noise Skeleton Image segmentation Remote sensing Accuracy

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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 new contour tracing method in a binary image

A new contour tracing method in a binary image

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International Conference on Multimedia Technology

作者： Lie Kang Sheng Zhong Fang Wang State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781612847719

This paper presents a novel fast single-pass contour tracing algorithm in a binary image. The proposed algorithm is viewed as follow steps: firstly a set of contour segments of all object contours can be generated and traced in a top-down line scan fashion; then all contour segments are employed to be integrated into respective intact contours; finally all results are converted into the chain code as the final output. This algorithm can extract multiple contours of an image in one pass and never lose any outer and inner contour of object region. It is faster on implementation. Experiments results prove those advantages.

关键词： Algorithm design and analysis Image segmentation Signal processing algorithms Shape Labeling Lakes pattern recognition

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A novel method concerning about image transition region extraction and segmentation

A novel method concerning about image transition region extr...

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International Conference on Multimedia Technology

作者： Fang Wang Tianxu Zhang Jinpeng Deng State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

According to the feature that the gray distribution of the transition region (locating between the objects and the background) is more scattered than that of the regions of targets or background in an image, this paper proposes a novel method concerning about transition region extraction and segmentation, which is based on local variance of different areas of an image. The experiments indicate that the proposed approach can achieve better segmentation results than the local complexity method (one of the previous methods for extracting transition region).What's more, the novel approach outperforms the local complexity method about more complete and more accurate transition regions, less interference from backgrounds, more detail information of segmented targets, clearer and better segmented targets, easier calculation, and higher processing speed.

关键词： Image segmentation Complexity theory Feature extraction Histograms Data mining Image edge detection Gray-scale

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The construction of fractional differential gradient operator

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Journal of Computational information Systems 2011年第12期7卷 4328-4342页

作者： Yang, Zhuzhong Lang, Fangnian Yu, Xiaohong Zhang, Yu Chengdu University College of Electronics and Information Engineering Chengdu 610106 China Laboratory of Pattern Recognition and Intelligent Information Processing Chengdu 610106 China University of Electronic Science and Technology of China School of Electronic Engineering Chengdu 610054 China

Fractional calculus is relative to the traditional integer order calculus put forward, which is the order of calculus from integer orders extended to any order of the mathematical promotion. From the theoretical point of view, the fractional differential calculus signal processing order extended to any number from an integer, the ways and means of information processing were extended. This article is a tentative application of fractional differential theory in image processing. First, starting from a fractional differential filter, we obtained fractional differential equations of one-dimensional signal. Referencing methods of constructing integer order differential operators, we proposed the method of constructing fractional differential operators. When the number of fractional differential order as 1 or 2, the fractional differential is equal to the first or second order differential, that means the integer-order differential is a special case of fractional differential. Finally, the experimental results show that the image edge detection which based on fractional differential operator compare to the traditional first and second differential operators has a higher signal to noise ratio. This paper shows that, as the study of fractional differential, the application of fractional calculus in a wider area will be successful. Copyright © 2011 Binary information Press.

关键词： Differentiation (calculus)

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Double-Row Cascade Labeling Algorithm for Hyper-Scale Issue

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Procedia Engineering 2011年 15卷 4047-4051页

作者： Yebin Fan Hualong Zhao Department of Computer Science Huazhong University of Science and Technology National Key Laboratory of Science and Technology on Multi-Spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology

An efficient algorithm is presented to label the connected components in the case that the primary memory is smaller than the image data. Our algorithm uses only the memory of two image rows to label the huge image or any image larger than the available memory. The search path compression is a applied for improving the performance further. An extensive comparison with the state-of-art algorithms is proposed, both on random and real datasets. Our algorithm shows an impressive speedup, while the auxiliary memory is not required at all comparing with all competitors.

关键词： Connected components labeling page fault hyper-scalar union-find

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Overview of approaches for accelerating scale invariant feature detection algorithm

Overview of approaches for accelerating scale invariant feat...

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International Conference on Electric information and Control Engineering (ICEICE)

作者： Jing zhang Hongshi Sang Xubang Shen National Key Laboratory of Science and Technology on Multi-spectral Information Processing Institute for Pattern Recognition & Artificial Intelligence Huazhong University of Science and Technology Wuhan China

SIFT (Scale Invariant Feature Transform) is one of most popular approach for feature detection and matching. Many parallelized algorithms have been proposed to accelerate SIFT to apply into real-time systems. This paper divides the researches into three different categories, that is, optimizing parallel algorithms based on general purpose multi-core processors, designing customized multi-core processor dedicated for SIFT and implementing SIFT based FPGA (Field Programmable Gate Arrays). Overview of the three type researches and analysis of task-level parallelism are presented in this paper.

关键词： Feature extraction Pixel Multicore processing Parallel algorithms Field programmable gate arrays

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