DocumentCode
3057283
Title
Supervised classification of early perceptual structure in dot patterns
Author
Tuceryan, Mhran ; Jain, Anil K. ; Ahuja, Narendrn
Author_Institution
Dept. of Comput. Sci., Michigan State Univ., East Lansing, MI, USA
fYear
1992
fDate
30 Aug-3 Sep 1992
Firstpage
88
Lastpage
91
Abstract
A supervised algorithm for computing perceptual groupings in dot patterns is presented. The algorithm uses shape features of the polygons in the Voronoi tessellation of the input pattern. The training patterns identified by humans are used to obtain an initial nocontextual classification which is then refined by a probabilistic relaxation labeling
Keywords
computational geometry; feature extraction; image recognition; learning systems; probability; Voronoi tessellation; dot patterns; early perceptual structure; nocontextual classification; pattern recognition; polygons; probabilistic relaxation labeling; shape feature extraction; supervised classification; Computer science; Feature extraction; Humans; Labeling; Phase measurement; Shape; Tree graphs; US Department of Transportation;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1992. Vol.II. Conference B: Pattern Recognition Methodology and Systems, Proceedings., 11th IAPR International Conference on
Conference_Location
The Hague
Print_ISBN
0-8186-2915-0
Type
conf
DOI
10.1109/ICPR.1992.201728
Filename
201728
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