Title: Intramodal palmprint recognition using texture feature

Authors: Y.L. Malathi Latha; Munaga V.N.K. Prasad

Addresses: CSE Department, Swami Vivekananda Institute of Technology (SVIT), Secunderbaad-26, India ' Institute for Development and Research in Banking Technology (IDRBT), Castle Hills, Masab Tank, Hyderabad-57, India

Abstract: Palmprint technology is a new branch of biometrics used to identify an individual. Palmprint has rich set of features like palm lines, wrinkles, minutiae points, texture, ridges, etc. Several line and texture extraction techniques for palmprint have been extensively studied. This paper presents an intramodal authentication system based on texture information extracted from the palmprint using the Haralick features, 2D-Gabor and 2D-log Gabor filters. An individual feature vector is computed for a palmprint using the extracted texture information of each filter type. Performance of the system using three feature types is evaluated individually. Finally, we combine the three feature types using feature level fusion to develop an intramodal palmprint recognition system. The experiments are evaluated on a standard benchmark database (PolyU Database), and the results shows that significant improvement in terms of recognition accuracy and error rates with the proposed intramodal recognition system compared to individual representations.

Keywords: palmprints; Gabor filter; log-Gabor filter; intramodal authentication; Haralick features; feature level fusion; palmprint recognition; biometrics; texture features; feature extraction.

DOI: 10.1504/IJISDC.2017.082858

International Journal of Intelligent Systems Design and Computing, 2017 Vol.1 No.1/2, pp.168 - 185

Received: 07 Mar 2015
Accepted: 14 Feb 2016

Published online: 14 Mar 2017 *

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