Robust analysis of feature spaces: Color image segmentation

被引:340
作者
Comaniciu, D
Meer, P
机构
来源
1997 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS | 1997年
关键词
D O I
10.1109/CVPR.1997.609410
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A general technique for the recovery of significant image features is presented The technique is based on the mean shift algorithm, a simple nonparametric procedure for estimating density gradients. Drawbacks of the current methods (including robust clustering) are avoided Feature space of any nature carl De processed, and as an example, color image segmentation is discussed. The segmentation is completely autonomous, only its class is chosen by the user Thus, the same program can produce a high quality edge image, or provide, by extracting all the significant colors, a preprocessor for content-based query systems, A 512 x 512 color image is analyzed in less than 10 seconds on a standard workstation. Gray level images am handled as color images having only the lightness coordinate.
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收藏
页码:750 / 755
页数:6
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