Title : 
Fuzzy line snakes
         
        
            Author : 
Kersten, Paul R.
         
        
            Author_Institution : 
46860 Hilton Dr., Lexington Park, MD, USA
         
        
        
        
        
        
            Abstract : 
Closed flexible contours extracted from images to represent object outlines are often called snakes. This paper explores and extends snakes to extract contour features from images for modeling and pattern recognition. Many contour extraction algorithms have a common formulation as a constrained optimization problem. One version, called the constrained fuzzy clustering algorithm, links fuzzy clustering and snakes-the resulting contour being called a fuzzy snake. An extension of this result replaces the snake vertices with fuzzy line exemplars. The resulting structure is called a fuzzy line snake; some of its properties are discussed and an example is presented
         
        
            Keywords : 
edge detection; fuzzy set theory; optimisation; pattern clustering; closed flexible contour extraction; constrained fuzzy clustering algorithm; constrained optimization problem; fuzzy clustering; fuzzy line exemplars; fuzzy line snakes; modeling; object outline representation; pattern recognition; snake vertices; Clustering algorithms; Constraint optimization; Data mining; Eigenvalues and eigenfunctions; Feature extraction; Filters; Fuzzy sets; Pattern recognition; Prototypes; Robustness;
         
        
        
        
            Conference_Titel : 
Fuzzy Information Processing Society, 1999. NAFIPS. 18th International Conference of the North American
         
        
            Conference_Location : 
New York, NY
         
        
            Print_ISBN : 
0-7803-5211-4
         
        
        
            DOI : 
10.1109/NAFIPS.1999.781651