Face Image Retrieval Using Sparse Representation Classifier with Gabor-LBP Histogram

Face image retrieval is an important issue in the practical applications such as mug shot searching and surveillance systems. However, it is still a challenging problem because face images are fairly similar due to the same geometrical configuration of facial features. In this paper, we present a face image retrieval method which is robust to the variations of face image condition and with high accuracy. Firstly, we choose the Gabor-LBP histogram for face image representation. Secondly, we use the sparse representation classification for the face image retrieval. Using the Gabor-LBP histogram and sparse representation classifier, we achieved effective and robust retrieval results with high accuracy. Finally, experiments are conducted on ETRI and XM2VTS database to verify a proposed method. It showed rank 1 retrieval accuracy rate of 98.9% on ETRI face set, and of 99.3% on XM2VTS face set, respectively.