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Multi-resolution elongated CS-LDP with Gabor feature for face recognition

Multi-resolution elongated CS-LDP with Gabor feature for face recognition Centre-symmetric local derivative pattern (CS-LDP) algorithm is proposed to describe the local second-order derivative feature of texture. However, CS-LDP can only describe second-order derivative feature of texture on four directions and lost some discriminant information on other directions. Addressing such problems, this paper proposed multi-resolution elongated CS-LDP (ME-CS-LDP) to solve such problem. By increasing the number of directions, which can be implemented by increasing the sampling points on the ellipse radius with interpolation, multi-resolution elongated CS-LDP can provide more discriminant information on more directions. Furthermore, our proposed multi-resolution elongated CS-LDP is defined in ellipse field to depict some important ellipse part of faces, like eyes and mouth. Gabor filter plus ME-CS-LDP/weighed ME-CS-LDP is used for face recognition in this paper. The experiment results on the illumination subset of Yale B database, the subset of PIE illumination database and VALID face database have validated the effectiveness of the proposed method. Keywords: face recognition; Gabor filter; local binary pattern; multi-resolution elongated CS-LDP. Reference to this paper should be made as follows: Chen, X., Hu, F., Liu, Z., Huang, Q. and Zhang, J. (2016) `Multi-resolution elongated CS-LDP with Gabor feature for face recognition', Int. J. Biometrics, Vol. 8, No. 1, pp.19­32. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Biometrics Inderscience Publishers

Multi-resolution elongated CS-LDP with Gabor feature for face recognition

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Publisher
Inderscience Publishers
Copyright
Copyright © 2016 Inderscience Enterprises Ltd.
ISSN
1755-8301
eISSN
1755-831X
DOI
10.1504/IJBM.2016.077103
Publisher site
See Article on Publisher Site

Abstract

Centre-symmetric local derivative pattern (CS-LDP) algorithm is proposed to describe the local second-order derivative feature of texture. However, CS-LDP can only describe second-order derivative feature of texture on four directions and lost some discriminant information on other directions. Addressing such problems, this paper proposed multi-resolution elongated CS-LDP (ME-CS-LDP) to solve such problem. By increasing the number of directions, which can be implemented by increasing the sampling points on the ellipse radius with interpolation, multi-resolution elongated CS-LDP can provide more discriminant information on more directions. Furthermore, our proposed multi-resolution elongated CS-LDP is defined in ellipse field to depict some important ellipse part of faces, like eyes and mouth. Gabor filter plus ME-CS-LDP/weighed ME-CS-LDP is used for face recognition in this paper. The experiment results on the illumination subset of Yale B database, the subset of PIE illumination database and VALID face database have validated the effectiveness of the proposed method. Keywords: face recognition; Gabor filter; local binary pattern; multi-resolution elongated CS-LDP. Reference to this paper should be made as follows: Chen, X., Hu, F., Liu, Z., Huang, Q. and Zhang, J. (2016) `Multi-resolution elongated CS-LDP with Gabor feature for face recognition', Int. J. Biometrics, Vol. 8, No. 1, pp.19­32.

Journal

International Journal of BiometricsInderscience Publishers

Published: Jan 1, 2016

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