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A novel method for 2D nonrigid partial shape matching.

Authors :
Yang, Chengzhuan
Wei, Hui
Yu, Qian
Source :
Neurocomputing. Jan2018, Vol. 275, p1160-1176. 17p.
Publication Year :
2018

Abstract

There are two categories of partial shape matching problem: whole-to-part matching and part-to-part matching. The first establishes the best match between an open curve and a part of a closed curve, while the second is to find a part of the first input closed curve that can be well aligned with a part of the second input closed curve. In this paper, we present a novel approach to solve these two categories of the partial shape matching problem. First, we propose a novel shape descriptor, triangular centroid distances (TCDs), for shape representation; the TCDs shape descriptor is invariant to translation, rotation, scaling, and considerable shape deformations. Then, using the TCDs shape descriptor, we present a method to deal with the whole-to-part partial shape matching problem. Finally, we extend our work to part-to-part partial shape matching. Here, we propose a new approach, again using the TCDs shape descriptor, to solve the part-to-part partial shape matching problem. Experimental results demonstrate that our method outperforms existing methods in 2D nonrigid partial shape matching. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09252312
Volume :
275
Database :
Academic Search Index
Journal :
Neurocomputing
Publication Type :
Academic Journal
Accession number :
126959203
Full Text :
https://doi.org/10.1016/j.neucom.2017.09.067