Automatic color space selection for biological image segmentation

被引:9
|
作者
Meas-Yedid, V [1 ]
Glory, E [1 ]
Morelon, E [1 ]
Pinset, C [1 ]
Stamon, G [1 ]
Olivo-Marin, JC [1 ]
机构
[1] Inst Pasteur, Quantitat Image Anal Unit, F-75015 Paris, France
来源
PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 3 | 2004年
关键词
D O I
10.1109/ICPR.2004.1334579
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper we have tested criteria designed by Liu and Borsotti to automatically evaluate the quality of a color segmentation. As they do not correctly answer our microscopy image problems, we propose two modified criteria adapted to two different biological applications. Penalizing inhomogeneity, numerous small regions and misclassified regions, our modified criteria help to select the best color space, for a given segmentation method.
引用
收藏
页码:514 / 517
页数:4
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