
Proceedings Paper
Multiscale image segmentation algorithm based on mean shiftFormat | Member Price | Non-Member Price |
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Paper 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.
Paper Details
Date Published: 31 July 2002
PDF: 7 pages
Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); doi: 10.1117/12.477156
Published in SPIE Proceedings Vol. 4875:
Second International Conference on Image and Graphics
Wei Sui, Editor(s)
PDF: 7 pages
Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); doi: 10.1117/12.477156
Show Author Affiliations
Fei Liu, Tsinghua Univ. (China)
Xiaodan Song, Tsinghua Univ. (China)
Xiaodan Song, Tsinghua Univ. (China)
Yupin Luo, Tsinghua Univ. (China)
Dongcheng Hu, Tsinghua Univ. (China)
Dongcheng Hu, Tsinghua Univ. (China)
Published in SPIE Proceedings Vol. 4875:
Second International Conference on Image and Graphics
Wei Sui, Editor(s)
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