DocumentCode :
1889605
Title :
Geometrical Algorithms to Detect Patterns from a Set of Points
Author :
Bougleux, Sébastien ; Melkemi, Mahmoud ; Elmoataz, Abderrahim
Author_Institution :
GREYC CNRS, Caen
fYear :
2006
fDate :
2-5 July 2006
Firstpage :
94
Lastpage :
101
Abstract :
This article presents a new approach for detecting patterns, such as lines, parabolas and circles, from a two- dimensional cloud of points S. This scheme transforms the problem of detecting the patterns from S, to the problem of detecting simpler patterns from a set of points S1 computed from the Voronoi and Delaunay diagrams of S. It is based on the differential properties of the Voronoi diagram that reflect the patterns to be retrieved. For example, in the case of parabolas, the patterns to be detected in S´ are straight lines. The general idea of using the Voronoi diagram to detect patterns is an alternative and a complementary approach to the Hough Transform. It does not need to code a space of parameters and can be generalized to higher dimensions, with some adaptations.
Keywords :
Hough transforms; computational geometry; mesh generation; pattern recognition; Delaunay diagram; Hough transform; Voronoi diagram; geometrical algorithm; pattern detection; point cloud cluster group; point set; two-dimensional point cloud; Cloud computing; Computer vision; Equations; Face detection; Image reconstruction; Noise shaping; Pattern analysis; Robustness; Shape; Voting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Voronoi Diagrams in Science and Engineering, 2006. ISVD '06. 3rd International Symposium on
Conference_Location :
Banff, Alberta, BC
Print_ISBN :
0-7695-2630-6
Type :
conf
DOI :
10.1109/ISVD.2006.23
Filename :
4124808
Link To Document :
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