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Image Segmentation Based on Support Vector Machine

XU Hai-xiang ZHU Guang-xi TIAN Jin-wen ZHANG Xiang PENG Fu-yuan

中国电子科技2005，Vol.3Issue(3)：226-230,5.

Image Segmentation Based on Support Vector Machine

XU Hai-xiang ¹ZHU Guang-xi ¹TIAN Jin-wen ²ZHANG Xiang ²PENG Fu-yuan¹

作者信息

1. Department of Electronics and Information Engineering, Huazhong University of Science and Technology Wuhan 430074 China
2. Institute of Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology Wuhan 430074 China
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摘要

Abstract

Image segmentation is a necessary step in image analysis. Support vector machine (SVM) approach is proposed to segment images and its segmentation performance is evaluated.Experimental results show that: the effects of kernel function and model parameters on the segmentation performance are significant; SVM approach is less sensitive to noise in image segmentation; The segmentation performance of SVM approach is better than that of back-propagation multi-layer perceptron (BP-MLP) approach and fuzzy c-means (FCM) approach.

关键词

support vector machine/image segmentation/image analysis

Key words

support vector machine/image segmentation/image analysis

分类

信息技术与安全科学

引用本文复制引用

XU Hai-xiang,ZHU Guang-xi,TIAN Jin-wen,ZHANG Xiang,PENG Fu-yuan..Image Segmentation Based on Support Vector Machine[J].中国电子科技,2005,3(3):226-230,5.

基金项目

Supported by the National Natural Science Foundation of China (No. 60475024) （No. 60475024）

中国电子科技

ISSN：1674-862X

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