DocumentCode :
3419724
Title :
An Improved Geometric Deformable Model for Color Image Segmentation
Author :
Huang, Shiguo ; Zhou, Mingquan ; Geng, Guohua
Author_Institution :
Visualization Inst., Northwest Univ., Xi´´an
fYear :
2006
fDate :
Nov. 2006
Firstpage :
513
Lastpage :
517
Abstract :
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
Keywords :
computational geometry; edge detection; image colour analysis; image segmentation; Di Zenzo multivalued geometry; color image segmentation; edge detector; geodesic active contour; geometric deformable model; Active contours; Color; Deformable models; Detectors; Image edge detection; Image segmentation; Level set; Parametric statistics; Solid modeling; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Reality and Telexistence--Workshops, 2006. ICAT '06. 16th International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
0-7695-2754-X
Type :
conf
DOI :
10.1109/ICAT.2006.39
Filename :
4089303
Link To Document :
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