Identifying Three-Dimensional Palmprints With Modified Four-Patch Local Binary Pattern (MFPLBP)

Abstract

Palmprint biometrics is the best method of identifying an individual with a unique palmprint for every person.The present paper formulates a new methodology towardsthe identification of 3D palmprints using the Modified FourPatch Local Binary Pattern (MFPLBP). It improves upon theconventional Four-Patch Local Binary Pattern (FPLBP) by integrating the adaptive weight with the improved texture extraction.Both approaches are created to support the intricate surfaceinformation of 3D palmprints. The MFPLBP can exactly capturelocal variations and is noise and illumination invariant. Thereare extensive experiments done in this paper and establish thatMFPLBP outperforms traditional LBP methods and other stateof-the-art methods in recognition rates. The experiments establishthat MFPLBP is a efficient and effective method of making useof 3D palmprints in real-world biometric verificatio