Multiscale image segmentation algorithm based on mean shift

Fei Liu; Xiaodan Song; Yupin Luo; Dongcheng Hu

doi:10.1117/12.477156

31 July 2002 Multiscale image segmentation algorithm based on mean shift

Fei Liu, Xiaodan Song, Yupin Luo, Dongcheng Hu

Proceedings Volume 4875, Second International Conference on Image and Graphics; (2002) https://doi.org/10.1117/12.477156
Event: Second International Conference on Image and Graphics, 2002, Hefei, China

Abstract

In this paper, we propose a multi-scale image segmentation algorithm based on mean shift, a simple iterative procedure that shifts each data point to the average of data points in its neighborhood, which has been proven to be a mode-seeking process on a surface constructed with a "shadow" kernel. In the presented algorithm, not only the color features, but also the space relationship of each pixel are considered in multiple scales, thus getting a more reasonable clustering sequence, furthermore, center candidates are validated by contour map. Experimental examples are illustrated and compared to show that the approach is effective not only in segmentation, but also in denoising.

Citation Download Citation

Fei Liu, Xiaodan Song, Yupin Luo, and Dongcheng Hu "Multiscale image segmentation algorithm based on mean shift", Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); https://doi.org/10.1117/12.477156

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