Local binary pattern domain local appearance face recognition

This paper presents a fast face recognition algorithm that combines the discrete cosine transform based local appearance face recognition technique with the local binary pattern (LBP) representation of the face images. The underlying idea is to benefit from both the robust image representation capability of local binary patterns, and the compact representation capability of local appearance-based face recognition. In the proposed method, prior to local appearance modeling, the input face image is transformed into the local binary pattern domain. The obtained LBP-representation is then decomposed into non-overlapping blocks and on each local block the discrete cosine transform is applied to extract the local features. The extracted local features are then concatenated to construct the overall feature vector. The proposed algorithm is tested extensively on the face images from the CMU PIE and the FRGC version 2 face databases. The experimental results show that the combined approach improves the performance significantly.