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Illumination-robust local pattern descriptor for face recognition

Title
Illumination-robust local pattern descriptor for face recognition
Authors
Kim, Dong-JuLee, Sang-HeonShon, Myoung-KyuKim, HyundukRyu, Nuri
DGIST Authors
Lee, Sang-HeonShon, Myoung-Kyu
Issue Date
2014
Citation
5th FTRA International Conference on Computer Science and its Applications, CSA 2013, 279 LNEE, 185-190
Type
Conference
Article Type
Conference Paper
ISBN
9780000000000
ISSN
1876-1100
Abstract
In this paper, we propose a simple descriptor called an extended center-symmetric pattern (ECSP) for illumination-robust face recognition. The ECSP operator encodes the texture information of a local face region by emphasizing diagonal components of a previous center-symmetric local binary pattern (CS-LBP). Here, the diagonal components are emphasized because facial textures along the diagonal direction contain much more information than those of other directions. The facial texture information of the ECSP operator is then used as the input image of an image covariance-based feature extraction algorithm. Performance evaluation of the proposed approach was carried out using various binary pattern operators and recognition algorithms on the extended Yale B database. The experimental results demonstrated that the proposed approach achieved better recognition accuracy than other approaches, and we confirmed that the proposed approach is effective against illumination variation. © 2014 Springer-Verlag Berlin Heidelberg.
URI
http://hdl.handle.net/20.500.11750/5497
DOI
10.1007/978-3-642-41674-3_28
Publisher
Springer Verlag
Related Researcher
Files:
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Collection:
Convergence Research Center for Future Automotive Technology2. Conference Papers


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