期刊
PATTERN RECOGNITION
卷 46, 期 7, 页码 1949-1963出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2013.01.003
关键词
Local descriptor; Region description; Orthogonal combination of local binary patterns; Color LBP descriptor; CS-LBP; SIFT; Image matching; Object recognition; Scene classification
资金
- French research agency ANR through the VideoSense project [2009 CORD 026 02]
Visual content description is a key issue for machine-based image analysis and understanding. A good visual descriptor should be both discriminative and computationally efficient while possessing some properties of robustness to viewpoint changes and lighting condition variations. In this paper, we propose a new operator called the orthogonal combination of local binary patterns (denoted as OC-LBP) and six new local descriptors based on OC-LBP enhanced with color information for image region description. The aim is to increase both discriminative power and photometric invariance properties of the original LBP operator while keeping its computational efficiency. The experiments in three different applications show that the proposed descriptors outperform the popular SIFT, CS-LBP, HOG and SURF, and achieve comparable or even better performances than the state-of-the-art color SIFT descriptors. Meanwhile, the proposed descriptors provide complementary information to color SIFT, because a fusion of these two kinds of descriptors is found to perform clearly better than either of the two separately. Moreover, the proposed descriptors are about four times faster to compute than color SIFT. (C) 2013 Elsevier Ltd. All rights reserved.
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