Infrared Face Recognition Based on Adaptive Dominant Pattern of Local Binary Pattern

Abstract

Abstract. Infrared face recognition, being light-independent, and not vulnerable to facial skin, expressions and posture, can avoid or limit the drawbacks of face recognition in visible light. Local binary pattern (LBP), as a classic local feature descriptor, is appreciated for infrared face feature representation. To extract compact and principle information from LBP features, infrared face recognition based on LBP adaptive dominant pattern is proposed in this paper. Firstly, LBP operator is applied to infrared face for texture information. Based on the statistical distribution, the variable dominant pattern is attained for different infrared faces. Finally, dissimilarity metrics between the adaptive dominant pattern features is defined for final recognition. The experimental results show the adaptive dominant patterns in infrared face image have a lower feature dimensionality, and the proposed infrared face recognition method outperforms the traditional methods based on LBP uniform and discriminant patterns.