Infrared face recognition based on local binary pattern and multi-objective genetic algorithm

To extract the discrimination local structural features, an improved infrared face recognition method based on LBP is proposed in this paper. To get robust local features in infrared face, local binary pattern representation is applied to our method, instead of holistic feature extraction method. The main drawback of LBP patterns representation is that the dimension of LBP pattern features is relatively high. Feature selection algorithm based on multi-objective genetic algorithm (MOGA) is proposed to analyze and discard patterns that are not relevant to the recognition task. The experimental results demonstrate the infrared face recognition method based on LBP+MOGA proposed outperforms the traditional methods based on LBP or PCA+LDA.