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A Robust and Compact Descriptor Based on Center-Symmetric LBP

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2 Author(s)
Jinwei Xiao ; State Key Lab. for Novel Software Technol., Nanjing Univ., Nanjing, China ; Gangshan Wu

Center-symmetric local binary pattern (CS-LBP) is a novel texture feature which utilizes texture to describe the local regions. It combines the good property of local binary pattern (LBP) and SIFT. It has been extended to a region descriptor and achieved promising performance in many applications. However, it is sensitive to noise and less efficient due to its high dimensional descriptor vector. Due to these, we propose a novel descriptor based on CS-LBP operator denoted as PCA-CS-LBP. Our proposed descriptor achieves better noise robustness using the difference of pixels instead of the rough comparing of pixels. Besides, PCA is employed and applied to generate a more compact representation. Comparisons between our descriptor and standard CS-LBP descriptor are given on a standard image matching dataset. Experimental results show that our descriptor is outperforms the standard CS-LBP descriptor in most cases.

Published in:

Image and Graphics (ICIG), 2011 Sixth International Conference on

Date of Conference:

12-15 Aug. 2011