A novel method for 2D nonrigid partial shape matching

2018 ◽  
Vol 275 ◽  
pp. 1160-1176 ◽  
Author(s):  
Chengzhuan Yang ◽  
Hui Wei ◽  
Qian Yu
2017 ◽  
Vol 36 (2) ◽  
pp. 247-258 ◽  
Author(s):  
O. Litany ◽  
E. Rodolà ◽  
A. M. Bronstein ◽  
M. M. Bronstein

2015 ◽  
Vol 26 (6) ◽  
pp. 711-721 ◽  
Author(s):  
Huijie Fan ◽  
Yang Cong ◽  
Yandong Tang

2018 ◽  
Vol 77 (20) ◽  
pp. 27405-27426 ◽  
Author(s):  
Zhengbing Wang ◽  
Guili Xu ◽  
Yuehua Cheng ◽  
Ruipeng Guo ◽  
Zhengsheng Wang

Author(s):  
Yu Cao ◽  
Zhiqi Zhang ◽  
Irina Czogiel ◽  
Ian Dryden ◽  
Song Wang

2011 ◽  
Vol 341-342 ◽  
pp. 785-789
Author(s):  
Yu Feng Chen ◽  
Chuan Qi Tan ◽  
Feng Xia Li ◽  
Qing Yi Zhang

In this paper, a novel method is proposed for solving an open problem of shape matching in content-based image retrieval. Our method regards the stack-triangles geometrics histogram to be the feature of an image, the correlation of two images was decided by the compare result of their stack-triangles geometrics histograms. First of all, these methods extract the key contour fragments of an image, so that a shape can be presented as many key contour fragments in this way. In addition, we derivation stack triangles of a shape by the key contour fragments we get it before. Then, we can get the stack-triangles geometrics histogram of the image and calculate the correlation of two images use their stack-triangles geometrics histogram. Finally, experiment results show that our new method is a very fast method and can get more robustness than existing methods and achieve a good effect in the standard shape databases MPEG-7.


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