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.
         
        
        
        
        
        
            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;
         
        
        
        
            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
         
        
        
            DOI : 
10.1109/ICMA.2006.257609