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Eigen Palmprint Identification Algorithm using PCA(Principal Components Analysis)  

Noh Jin-Soo (Dept. of Electronic Engineering, Chosun University)
Rhee Kang-Hyeon (Dept. of Electronic Engineering, Chosun University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.43, no.3, 2006 , pp. 82-89 More about this Journal
Abstract
Palmprint-based personal identification system, as a new member in the biometrics system family, has become an active research topic in recent years. Although lots of methods have been made, how to represent palmprint for effective classification is still an open problem and conducting researches. In this paper, the palmprint classification and recognition method based on PCA (Principal Components Analysis) using the dimension reduction of singular vector is proposed. And the 135dpi palmprint image which is obtained by the palmprint acquisition device is used for the effectual palmprint recognition system. The proposed system is consists of the palmprint acquisition device, DB generation algorithm and the palmprint recognition algorithm. The palmprint recognition step is limited 2 times. As a results GAR and FAR are 98.5% and 0.036%.
Keywords
Palmprint; Principal Components Analysis; Dimension Reduction; Identification; Eigen Vector;
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