Title : 
A deformable model-based image segmentation algorithm for shapes with corners
         
        
            Author : 
Zhang, Zixin ; Braun, Michael
         
        
            Author_Institution : 
Dept. of Appl. Phys., Univ. of Technol., Sydney, NSW, Australia
         
        
        
        
        
        
            Abstract : 
Deformable models are generally applied to simple images with smooth region boundaries. Segmentation of objects with high curvature shapes (corners) is limited by the models´ finite node density and their intrinsic smoothness constraint. Previous solutions to segmentation of objects with corners are based on relating the smoothness constraint at the candidate corner nodes. While allowing a contour to bend at those nodes, these solutions do not provide a force to propel nodes into corners. In this paper, we propose a deformable model algorithm for segmenting objects containing high curvature shapes with subresolution accuracy, which provides a driving force for nodes to slide into corners along object boundaries. The algorithm can be applied to both 2D and 3D deformable models
         
        
            Keywords : 
edge detection; image segmentation; mesh generation; stereo image processing; 2D deformable model; 3D deformable models; corner nodes; curvature shapes; image segmentation; object contour; triangular mesh; Active contours; Convergence; Deformable models; Energy measurement; Force measurement; Image segmentation; Physics; Scalability; Shape;
         
        
        
        
            Conference_Titel : 
Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
         
        
            Conference_Location : 
Brisbane, Qld.
         
        
        
            Print_ISBN : 
0-8186-8512-3
         
        
        
            DOI : 
10.1109/ICPR.1998.711163