DocumentCode :
2865386
Title :
An Image Segmentation Method Based on the Improved Snake Model
Author :
Wang, Kejun ; Guo, Qingchang ; Zhuang, Dayan
Author_Institution :
Dept. of Autom., Harbin Eng. Univ.
fYear :
2006
fDate :
25-28 June 2006
Firstpage :
532
Lastpage :
536
Abstract :
Getting the contour of the object based on the snake model is an important method in the image segmentation. In this paper the authors first introduce the theory of the traditional snake model. A new snake model based on a dot which is in the object is proposed for avoiding some drawbacks in the traditional snake model. The algorithm not only inherits the topology ability of the traditional snake, but also has the ability of convergence to the concave, and the convergent rate is also added. The segmentation effort of the algorithm is proved by experiments
Keywords :
computer vision; image segmentation; topology; concave convergence; image segmentation; object contour; snake model; topology; Active contours; Automation; Convergence; Equations; Image converters; Image segmentation; Mechatronics; Solid modeling; Topology; snake model image segmentation topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation, Proceedings of the 2006 IEEE International Conference on
Conference_Location :
Luoyang, Henan
Print_ISBN :
1-4244-0465-7
Electronic_ISBN :
1-4244-0466-5
Type :
conf
DOI :
10.1109/ICMA.2006.257609
Filename :
4026139
Link To Document :
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