Discriminative BULBPH Descriptor with KDA for Palmprint Recognition

0Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

Abstract

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.

Cite

CITATION STYLE

APA

Tamrakar, D., & Khanna, P. (2020). Discriminative BULBPH Descriptor with KDA for Palmprint Recognition. In Advances in Intelligent Systems and Computing (Vol. 1022 AISC, pp. 423–435). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-32-9088-4_35

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free