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Proceedings Paper

Segmentation of colonscopic images based on the fusion of multiple features
Author(s): Shunren Xia; Danqi Zhu; Xiaomin Lou; Leping Zhou; Guoxiong Zhang
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Paper Abstract

A new algorithm for segmenting color colonscopic images by fusing color, brightness, spatial distance and texture information is presented in this paper. It makes the fractal dimension (FD) as the measurement for texture feature in images and applies a stochastic clustering algorithm that uses pairwise similarity of elements. The clustering algorithm that is based on a new graph theoretical algorithm for the sampling of cuts in graphs, can obtain the optimal number of clusters automatically. The complexity of our method is lower, and its stochastic nature makes it robust against noise. More than 40 colonscopic images have been used to demonstrate the effectiveness of this new algorithm.

Paper Details

Date Published: 25 September 2003
PDF: 6 pages
Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); doi: 10.1117/12.539073
Show Author Affiliations
Shunren Xia, Zhejiang Univ. (China)
Danqi Zhu, Zhejiang Univ. (China)
Xiaomin Lou, Hangzhou Hospital of Traditional Chinese Medicine (China)
Leping Zhou, Hangzhou Hospital of Traditional Chinese Medicine (China)
Guoxiong Zhang, Hangzhou Hospital of Traditional Chinese Medicine (China)


Published in SPIE Proceedings Vol. 5286:
Third International Symposium on Multispectral Image Processing and Pattern Recognition
Hanqing Lu; Tianxu Zhang, Editor(s)

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