Title :
Weighted Boundary Points for Shape Analysis
Author :
Zhang, Jing ; Kasturi, Rangachar
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA
Abstract :
Shape analysis is an active and important branch in computer vision research field. In recent years, many geometrical, topological, and statistical features have been proposed and widely used for shape-related applications. In this paper, based on the properties of Distance Transform, we present a new shape feature, weight of boundary point. By computing the shortest distances between boundary points and distance contours of a transformed shape, every boundary point is assigned a weight, which contains the interior structure information of the shape. To evaluate the proposed new shape feature, we tested the weighted boundary points on shape matching and shape decomposition. The experimental results demonstrated the validity.
Keywords :
computer vision; image matching; shape recognition; transforms; computer vision; distance transform; shape analysis; shape decomposition; shape matching; shape-related application; weighted boundary point; Computer vision; Context; Feature extraction; Pattern analysis; Shape; Three dimensional displays; Transforms; distance transform; shape decomposition; shape matching; weighted boundary points;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.395