High Performance Palmprint Identification System Based On Two Dimensional Gabor
Abstract: The palmprint is a
new recognition method in physiological biometrics. In palmprint region of
interest (ROI), the segmentation and feature extraction are two important
issues. The main problem in palmprint recognition system is how to extract the
region of interest (ROI) and the features of palmprint. This paper introduces
two steps in center of mass moment and the application of method for ROI
segmentation and then to apply the Gabor two dimensional (2D) filters to obtain
palm code as palmprint feature vector. Normalized Hamming distance is used to
measure the similarity degrees of two feature vectors of palmprint. The system
has been tested by using database 1000 palmprint images which was generated
from 5 groups of samples from 200 persons selected randomly. Experiment results
show that this system can achieve a high performance with success rate about
98.7% (FRR=1.1667%, FAR=0.1111%, T=0.376).
Penulis: I Ketut Gede Darma
Putra, Erdiawan
Kode Jurnal: jptkomputerdd100055
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