Palmprint and Palm Vein Multimodal Fusion Biometrics Based on MMNBP

This paper presents a multi-biometrics recognition method based on the fusion of palmprint and palm vein. Firstly, the traditional LBP method is improved, a novel algorithm called neighbor based binary pattern (NBP) is presented, which uses the relationship of gray value between adjacent pixels in the local area to encode the image. Secondly, the images of palm vein and palmprint are subdivided into several uniform size blocks, the gray mean value of each block is calculated. Furtherly, the multi-block mean image is encoded by the NBP method, which is called multi-block mean neighbor based binary pattern (MMNBP), and the feature fusion operation is implemented. Finally, the Hamming distance is used for matching. The comparison experiments are carried out with the current typical and popular approaches in the PolyU contact public database and self-built non-contact database. The experimental results indicate the superiority and effectiveness of the approach, which has good application prospect.