Volume : 2, Issue : 2, February - 2013

Multifeature–Based HR (High–Resolution) Palmprint Recognition

S. Gandhimathi, P. Narendran

Abstract :

There has been a high demand for personal identification and verification for security reasons. Biometric computing o4ers an effective approach to identify personal identity by using individual’s unique, reliable and stable physical or behavioral characteristics. The main importance of biometrics includes the positive authentication and verification of a person and ensuring confidentiality of information in storage or in transit. In the field of biometrics, palmprint is a novel but promising technology. Palmprint recognition has considerable potential as a personal identification technique. But for high–security applications (e.g., forensic usage), high–resolution palmprints (500 ppi or higher) are required from which more useful information can be extracted. In this paper, we propose a novel recognition algorithm for high–resolution palmprint. This research work mainly focuses on the usage of a novel fusion scheme for an identification application which performs better than conventional fusion methods. Extreme Learning Machine is used in this approach for novel fusion approach. The performance of the proposed approach is compared with the existing novel fusion approaches such as SVM, Neyman–Pearson rule.