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Haar-like compact local binary pattern for illumination-robust feature matching

[+] Author Affiliations
Bongjoe Kim

Yonsei University, Department of Electrical and Electronic Engineering, 134 Shinchon-dong, Seodaemun-gu, Seoul 120-749, Republic of Korea

Jihoon Choi

Agency for Defense Development, Daejeon 305-152, Republic of Korea

Sanghyun Joo

Agency for Defense Development, Daejeon 305-152, Republic of Korea

Kwanghoon Sohn

Yonsei University, Department of Electrical and Electronic Engineering, 134 Shinchon-dong, Seodaemun-gu, Seoul 120-749, Republic of Korea

J. Electron. Imaging. 21(4), 043014 (Nov 22, 2012). doi:10.1117/1.JEI.21.4.043014
History: Received May 6, 2012; Revised September 15, 2012; Accepted October 22, 2012
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Abstract.  A novel method for local image descriptor called a Haar-like compact local binary pattern (HC-LBP) is presented, which is robust to Gaussian noise and illumination changes and reduces the dimension of features by modifying the local binary pattern (LBP) method in two ways. First, the binary Haar-like feature method is applied to calculate region-based rank order. The binary Haar-like feature method maintains only the ordinal relationship and not the difference of intensity. Using a region-based binary operation, the proposed local image descriptor becomes more robust to Gaussian noise and illumination changes. Second, a HC-LBP feature is generated by applying the binary Haar-like feature according to the edge class in order to reduce feature dimensions and increase the discriminating power of each feature. In the feature matching experiment, the proposed method outperforms the popular scale invariant feature transform, center-symmetric local binary pattern and center-symmetric local ternary pattern in the presence of illumination changes, Gaussian noise, image blurring, and viewpoint change. Compared with popular local feature descriptors, the proposed method could get more than 0.1 increases in recall. Also, the HC-LBP descriptor could be used for many computer vision applications such as image retrieval, face recognition, and texture recognition.

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© 2012 SPIE and IS&T

Citation

Bongjoe Kim ; Jihoon Choi ; Sanghyun Joo and Kwanghoon Sohn
"Haar-like compact local binary pattern for illumination-robust feature matching", J. Electron. Imaging. 21(4), 043014 (Nov 22, 2012). ; http://dx.doi.org/10.1117/1.JEI.21.4.043014


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