XU Hai-xiang, ZHU Guang-xi, TIAN Jin-wen, ZHANG Xiang, PENG Fu-yuan. Image Segmentation Based on Support Vector Machine[J]. Journal of Electronic Science and Technology, 2005, 3(3): 226-230.
Citation: XU Hai-xiang, ZHU Guang-xi, TIAN Jin-wen, ZHANG Xiang, PENG Fu-yuan. Image Segmentation Based on Support Vector Machine[J]. Journal of Electronic Science and Technology, 2005, 3(3): 226-230.

Image Segmentation Based on Support Vector Machine

Funds: 

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

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  • Author Bio:

    XU Hai-xiang research interests include: image processing; pattern recognition and artificial intelligence, qukaiyang@163.com.

  • Received Date: 2004-11-09
  • Publish Date: 2005-09-24
  • 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.
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