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Proceedings Paper

Perceptually clustering color for image segmentation
Author(s): Hualin Wan; Hong Hu; Zhongzhi Shi
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Paper Abstract

Color image segmentation is very important to machine vision, image understanding, and content-based image retrieval, etc, but there are few automatic and effective algorithms that can work fast and well on natural scene image. In this paper, we propose a new automatic color image segmentation algorithm using perceptually color clustering in Munsell(HVC) color space. Above all, we introduce the conversion formulae from (R, G, B) to (H, V, C) and the NBS color distance. Based on this, first, colors in the image are quantized to 256 colors or fewer without significantly degrading the color quality; then clustering the similar colors based on NBS color distance, finally, according to some rule, merging small color regions to its neighbor region.

Paper Details

Date Published: 24 September 2001
PDF: 6 pages
Proc. SPIE 4554, Object Detection, Classification, and Tracking Technologies, (24 September 2001); doi: 10.1117/12.441659
Show Author Affiliations
Hualin Wan, Institute of Computing Technology (China)
Hong Hu, Institute of Computing Technology (China)
Zhongzhi Shi, Institute of Computing Technology (China)

Published in SPIE Proceedings Vol. 4554:
Object Detection, Classification, and Tracking Technologies
Jun Shen; Sharatchandra Pankanti; Runsheng Wang, Editor(s)

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