Discriminative BULBPH Descriptor with KDA for Palmprint Recognition

  • Deepti Tamrakar
  • Pritee KhannaEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1022)


This work proposes Block-wise uniform local binary pattern histogram (BULBPH) followed by kernel discrimination analysis (KDA) as descriptor for palmprint recognition. BULBPH provides distribution of uniform patterns (such as line and wrinkles) in local region and can be better used as palmprint features. KDA is applied on BULBPH to reduce dimension and enhance discriminative capability using chi-RBF kernel. The experiments are conducted on four palmprint databases and performance is compared with related descriptors. It is observed that KDA on BULBPH descriptor achieves more than 99% accuracy with 4.04 decidability index on four palmprint databases.


Palmprint Blockwise uniform local binary pattern Kernel discriminant analysis 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Jabalpur Engineering CollegeJabalpurIndia
  2. 2.PDPM Indian Institute of Information Technology, Design and Manufacturing, JabalpurJabalpurIndia

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