Color image segmentation algorithm based on neural networks

Qizhi Teng; Xiaohai He; Li Jiang; Zhouyu Deng; Xiaoqiang Wu; Deyuan Tao

doi:10.1117/12.403953

11 October 2000 Color image segmentation algorithm based on neural networks

Qizhi Teng, Xiaohai He, Li Jiang, Zhouyu Deng, Xiaoqiang Wu, Deyuan Tao

Author Affiliations +

Proceedings Volume 4224, Biomedical Photonics and Optoelectronic Imaging; (2000) https://doi.org/10.1117/12.403953
Event: Optics and Optoelectronic Inspection and Control: Techniques, Applications, and Instruments, 2000, Beijing, China

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.

Citation Download Citation

Qizhi Teng, Xiaohai He, Li Jiang, Zhouyu Deng, Xiaoqiang Wu, and Deyuan Tao "Color image segmentation algorithm based on neural networks", Proc. SPIE 4224, Biomedical Photonics and Optoelectronic Imaging, (11 October 2000); https://doi.org/10.1117/12.403953

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