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