An improved geometric deformable model for color image segmentation

被引:0
作者
Huang, Shiguo [1 ]
Zhou, Mingquan
Geng, Guohua [1 ,2 ]
机构
[1] NW Univ Xian, Visualizat Inst, Xian 710069, Peoples R China
[2] NW Univ Xian, Xian, Peoples R China
来源
ICAT 2006: 16TH INTERNATIONAL CONFERENCE ON ARTIFICIAL REALITY AND TELEXISTENCE - WORSHOPS, PROCEEDINGS | 2006年
关键词
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
There were some difficulties when applying current geometric deformable models to color image segmentation. In order to solve the problem, different edge detectors are compared, and then CGAC-an improved geometric deformable model is developed by applying a new edge detector from Di Zenzo multivalued geometry of color image to GAC The experimental results show that when applying GAC channel by channel directly to color image segmentation, different boundaries of the same object represented by zero level sets in different channels can be obtained but they can not be identified which boundary is the exact boundary of object. On the contrary, when the evolution of zero level sets stops by applying CGAC, ideal boundary of object, which coincides with human perception, is obtained.
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页码:513 / +
页数:3
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