Abstract
Local binary pattern (LBP) is an effective local feature descriptor for infrared face representation. To extract discriminative subset in LBP patterns, infrared face recognition based on optimized discriminative patterns (ODP) is proposed in this paper. Firstly, LBP operator is applied to infrared face for the extraction of texture information. Secondly, based on the two-class discriminative ability, for each subject, we adaptively select the optimized discriminative patterns from LBP features. Then, dissimilarity metrics base on chi-square distance is computed for each two-classifier. Finally, the final recognition algorithm is built on all two-classifiers using voting mechanism. The experimental results show the ODP can extract compact and discriminative features for infrared face feature extraction, which outperform the existing LBP uniform and discriminative patterns.
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Xie, Z., Xiong, Y. (2015). Infrared Face Recognition Based on ODP of Local Binary Patterns. In: Yang, J., Yang, J., Sun, Z., Shan, S., Zheng, W., Feng, J. (eds) Biometric Recognition. CCBR 2015. Lecture Notes in Computer Science(), vol 9428. Springer, Cham. https://doi.org/10.1007/978-3-319-25417-3_21
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DOI: https://doi.org/10.1007/978-3-319-25417-3_21
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