DocumentCode :
3054404
Title :
Computing perceptual organization using voting methods and graphical enumeration
Author :
Sarkar, Sudeep ; Boyer, Kim L.
Author_Institution :
Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
fYear :
1992
fDate :
30 Aug-3 Sep 1992
Firstpage :
263
Lastpage :
267
Abstract :
Presents an efficient hierarchical computational paradigm for perceptual organization. Organization at each level of the hierarchy is done by graph enumeration on a set of Gestalt graphs. Efficient voting methods are proposed. The authors develop the method in detail and analyze its computational efficiency, considering both time and space. The theoretical and practical results are very encouraging. They strongly advocate the idea of an organizational hierarchy, constructed using graph enumeration. Graph theoretic representations enable one to extract various structures with considerable ease. They evaluated the performance using real images, with good results
Keywords :
computer vision; graph theory; image recognition; Gestalt graphs; graph theory; graphical enumeration; hierarchical computational paradigm; machine vision; pattern recognition; perceptual organization; voting methods; Detectors; Kilns; Laboratories; Signal analysis; Voting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1992. Vol.I. Conference A: Computer Vision and Applications, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2910-X
Type :
conf
DOI :
10.1109/ICPR.1992.201554
Filename :
201554
Link To Document :
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