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Communication Dans Un Congrès Année : 2006

Description of interest regions with center-symmetric local binary patterns

Résumé

Local feature detection and description have gained a lot ofinterest in recent years since photometric descriptors computed for interest regions have proven to be very successful in many applications. In this paper, we propose a novel interest region descriptor which combines the strengths of the well-known SIFT descriptor and the LBP texture operator. It is called the center-symmetric local binary pattern (CS-LBP) descriptor. This new descriptor has several advantages such as tolerance to illumination changes, robustness on flat image areas, and computational efficiency. We evaluate our descriptor using a recently presented test protocol. Experimental results show that the CS-LBP descriptor outperforms the SIFT descriptor for most of the test cases, especially for images with severe illumination variations.

Dates et versions

inria-00548586 , version 1 (20-12-2010)

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Marko Heikkila, Matti Pietikainen, Cordelia Schmid. Description of interest regions with center-symmetric local binary patterns. 5th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP '06), Dec 2006, Madurai, India. pp.58--69, ⟨10.1007/11949619_6⟩. ⟨inria-00548586⟩
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