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color image segmentation using automatic pixel classification with support vector machine
Wang Xiang-Yang; Wang Qin-Yan; Yang Hong-Ying; Bu Juan
2011
会议录名称Neurocomputing
页码-
收录类别ei
ISSN9252312
部门归属(1) School of Computer and Information Technology, Liaoning Normal University, Dalian 116029, China; (2) State Key Laboratory of Information Security, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China
摘要Automatic segmentation of images is a very challenging fundamental task in computer vision and one of the most crucial steps toward image understanding. In this paper, we present a color image segmentation using automatic pixel classification with support vector machine (SVM). First, the pixel-level color feature is extracted in consideration of human visual sensitivity for color pattern variations, and the image pixel's texture feature is represented via steerable filter. Both the pixel-level color feature and texture feature are used as input of SVM model (classifier). Then, the SVM model (classifier) is trained by using fuzzy c-means clustering (FCM) with the extracted pixel-level features. Finally, the color image is segmented with the trained SVM model (classifier). This image segmentation not only can fully take advantage of the local information of color image, but also the ability of SVM classifier. Experimental evidence shows that the proposed method has a very effective segmentation results and computational behavior, and decreases the time and increases the quality of color image segmentation in compare with the state-of-the-art segmentation methods recently proposed in the literature. © 2011 Elsevier B.V. All rights reserved.
关键词Behavioral Research Color Computer Vision Pixels Sensitivity Analysis Support Vector Machines Textures
语种英语
WOS记录号WOS:000296941200019
引用统计
被引频次:18[WOS]   [WOS记录]     [WOS相关记录]
内容类型会议论文
URI标识http://ir.iscas.ac.cn/handle/311060/14343
专题信息安全国家重点实验室
推荐引用方式
GB/T 7714
Wang Xiang-Yang,Wang Qin-Yan,Yang Hong-Ying,et al. color image segmentation using automatic pixel classification with support vector machine[C],2011:-.
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