Segmentation of colonscopic images based on the fusion of multiple features

Shunren Xia; Danqi Zhu; Xiaomin Lou; Leping Zhou; Guoxiong Zhang

doi:10.1117/12.539073

25 September 2003 Segmentation of colonscopic images based on the fusion of multiple features

Shunren Xia, Danqi Zhu, Xiaomin Lou, Leping Zhou, Guoxiong Zhang

Proceedings Volume 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition; (2003) https://doi.org/10.1117/12.539073
Event: Third International Symposium on Multispectral Image Processing and Pattern Recognition, 2003, Beijing, China

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.

Citation Download Citation

Shunren Xia, Danqi Zhu, Xiaomin Lou, Leping Zhou, and Guoxiong Zhang "Segmentation of colonscopic images based on the fusion of multiple features", Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); https://doi.org/10.1117/12.539073

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