Palmprint identification using PCA algorithm and hierarchical neural network

Authors:
Ling Lin
Affiliations:
Dept. of Computer Science, YiLi Normal College, Yining, China
Venue:
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
Year:
2010

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Abstract

Palmprint-based personal identification, as a new member in the biometrics family, has become an active research topic in recent years. The rich texture information of palmprint offers one of the powerful means in the field of personal recognition. In this paper, a novel approach for handprint identification is proposed. Firstly, region of interest is segmented through hand's key points localization, then PCA algorithm is used to extract the palmprint features. A hierarchical neural network structure is employed to measure the degree of similarity in the identification stage. Experimental results show that the designed system achieves an acceptable level of performance.