Computer Science ›› 2015, Vol. 42 ›› Issue (Z11): 146-150.

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Palmprint Recognition Based on Improved PCA and SVM

LI Kun-lun, ZHANG Ya-xin, LIU Li-li and GENG Xue-fei   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Palmprint recognition is an important part of biological feature recognition.Feature extraction and feature recognition are the main content of palmprint recognition.This paper made the improvement to the PCA algorithm based on principal component analysis.At first,palmprint image is processed by Fourier transform,and then the principal component analysis is used.Another method is that the palmprint image is processed by block principal component analysis.The improved feature extraction method was verified by the experiment.The results show that it can improve the recognition accuracy rate.In the aspect of feature recognition,although to a certain extent,template matching has small amount of calculation and high accuracy,it is easy to fall into the small sample size problem.This paper completed the palmprint recognition by training SVM classifier.Experimental results show that the method has better feasibility.

Key words: Palmprint recognition,Principal component analysis,Improved principal component analysis,Fourier transform,SVM classifier

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