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We introduce the sparse binary pattern (SBP),which is a feature extract method combined SRC with LBP.SBP is robust to illumination. In the paper, we put forward improvement in two directions: multi-value pattern and weighted pattern. Drawing lessons Finger Vein and Finger Dorsal Texture on LTP, we propose sparse ternary pattern (STP); considering different local block makes different contribution to finger vein and finger dorsal texture, we put forward the weighted sparse binary pattern (WSBP).Each improvement makes competitive results. At last, we consider the joint optimization of sparse multi-value pattern and Locally collaborative representation classification (LCRC),namely, we use sparse multi-value pattern in the feature extraction module and use or locally collaborative representation based classification (LCRC) in the classification module. The extensive experiments show that the joint optimization has more advantages than single optimization.

Finger Vein and Finger Dorsal Texture Recognition Joint Optimization based on Sparse Representation