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The Scientific World Journal
Volume 2015, Article ID 382697, 8 pages
http://dx.doi.org/10.1155/2015/382697
Research Article

Palm-Print Pattern Matching Based on Features Using Rabin-Karp for Person Identification

1Anna University of Technology, Trichy, Tamil Nadu, India
2Indra Ganesan College of Engineering, Trichy, Tamil Nadu, India

Received 20 April 2015; Revised 18 August 2015; Accepted 27 October 2015

Academic Editor: Michele Nappi

Copyright © 2015 S. Kanchana and G. Balakrishnan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Palm-print based individual identification is regarded as an effectual method for identifying persons with high confidence. Palm-print with larger inner surface of hand contains many features such as principle lines, ridges, minutiae points, singular points, and textures. Feature based pattern matching has faced the challenge that the spatial positional variations occur between the training and test samples. To perform effective palm-print features matching, Rabin-Karp Palm-Print Pattern Matching (RPPM) method is proposed in this paper. With the objective of improving the accuracy of pattern matching, double hashing is employed in RPPM method. Multiple patterns of features are matched using the Aho-Corasick Multiple Feature matching procedure by locating the position of the features with finite set of bit values as an input text, improving the cumulative accuracy on hashing. Finally, a time efficient bit parallel ordering presents an efficient variation on matching the palm-print features of test and training samples with minimal time. Experiment is conducted on the factors such as pattern matching efficiency rate, time taken on multiple palm-print feature matching efficiency, and cumulative accuracy on hashing.