DocumentCode :
2216134
Title :
Shape signature based on Homotopic deformation
Author :
Zhou, Li ; Jiang, Xinhua
Author_Institution :
Dept. of Inf. Sci., Central South Univ., Changsha, China
Volume :
1
fYear :
2010
fDate :
20-22 Aug. 2010
Abstract :
This paper proposes a new method for shape signature which is based on Homotopic deformation(HDBS). HDBS use the minimum circumcircle which encircle the shape as the deform template, and use the path length derived from deformation as the sampling data. This method ensures the disjoint among the paths of deformation, avoids crossing by paths and contours except at origin, every point in contour can be sampled, as a result, HDBS can accurately derive shape signature for the complex concave shapes. Moreover, our approach captures global features of shapes and is less sensitive to uneven noise. Through theoretical prove and experimental test, the signature data is not sensitive to position move, rotation and scale, and can be used in shape match directly.
Keywords :
image matching; shape recognition; homotopic deformation; minimum circumcircle; path length; shape match; shape signature; Artificial neural networks; Silicon; Constrained Delaunay Triangulation; Homotopic deformation; Minimum circumcircle; Shape signature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
ISSN :
2154-7491
Print_ISBN :
978-1-4244-6539-2
Type :
conf
DOI :
10.1109/ICACTE.2010.5579043
Filename :
5579043
Link To Document :
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