Perceptually clustering color for image segmentation

Hualin Wan; Hong Hu; Zhongzhi Shi

doi:10.1117/12.441659

24 September 2001 Perceptually clustering color for image segmentation

Hualin Wan, Hong Hu, Zhongzhi Shi

Proceedings Volume 4554, Object Detection, Classification, and Tracking Technologies; (2001) https://doi.org/10.1117/12.441659
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China

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.

Citation Download Citation

Hualin Wan, Hong Hu, and Zhongzhi Shi "Perceptually clustering color for image segmentation", Proc. SPIE 4554, Object Detection, Classification, and Tracking Technologies, (24 September 2001); https://doi.org/10.1117/12.441659

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