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Proceedings Paper

Color image segmentation algorithm based on neural networks
Author(s): Qizhi Teng; Xiaohai He; Li Jiang; Zhouyu Deng; Xiaoqiang Wu; Deyuan Tao
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Paper Abstract

This paper presents a color image segmentation method with Self-Organize Feature Map and General Learning Vector Quantity which, in the uniform color space, divides color into clusters based on the least sum of squares criterion. At the first step of this method, SOFM is employed to make a preliminary classification on the original image, and then GLVQ is used to segment it. Both of their advantages can be fully taken of to improve the precision and velocity of color image segmentation.

Paper Details

Date Published: 11 October 2000
PDF: 5 pages
Proc. SPIE 4224, Biomedical Photonics and Optoelectronic Imaging, (11 October 2000); doi: 10.1117/12.403953
Show Author Affiliations
Qizhi Teng, Sichuan Univ. (China)
Xiaohai He, Sichuan Univ. (China)
Li Jiang, Sichuan Univ. (China)
Zhouyu Deng, Sichuan Univ. (China)
Xiaoqiang Wu, Sichuan Univ. (China)
Deyuan Tao, Sichuan Univ. (China)


Published in SPIE Proceedings Vol. 4224:
Biomedical Photonics and Optoelectronic Imaging
Hong Liu; Qingming Luo, Editor(s)

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