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	Effective Selection of Mixed Color Features for Image Segmentation
	Luo ; Junfeng ; Ma ; Jinwen
	2016
关键词	segmentation histogram entropy Selection pixel benchmark challenging partitioning satisfactory overcome
英文摘要	Image segmentation is a basic task in image analysis and understanding and feature extraction is important but difficult. In this paper, we propose an effective feature selection method for color image segmentation which selects a group of mixed color features or channels from some different color spaces according to the principle of the least entropy of pixels frequency histogram distribution. Actually, 3 color channels that have the least entropies among all the channels in the whole alternative color spaces for a color image are selected to be our extracted mixed features. Publicly available segmentation database BSDS500 and 3 different segmentation algorithms are adopted to demonstrate the advantage and improvement of our selected mixed features on color image segmentation. Keywords:Feature selection, Image segmentation, Color space, Channel,Entropy.; IEEE Beijing Section、IET Beijing Local Network、Beijing Jiaotong University; 5
语种	英语
出处	知网
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/479730]
专题	数学科学学院
推荐引用方式 GB/T 7714	Luo,Junfeng,Ma,et al. Effective Selection of Mixed Color Features for Image Segmentation. 2016-01-01.

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