A Finger Vein Recognition Method Based on PCA-RBF Neural Network

Cheng Bo Yu; Jun Tan; Lei Yu; Yin Li Tian

doi:10.4028/www.scientific.net/AMM.325-326.1653

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 325-326A Finger Vein Recognition Method Based on PCA-RBF...

A Finger Vein Recognition Method Based on PCA-RBF Neural Network

Abstract:

This paper puts forward a finger vein classification algorithm which combines Principal Component Analysis (PCA) with Radial Basis Function (RBF) neural network algorithm, named the PCA-RBF algorithm. Use the training sample to reduce PCA dimensions, and abstract the main component of the image. Because of the advantages of RBF neural network classifying, put finger vein images into different classes, and then use the shortest distance to recognize. Through the experiment result comparing with Back Propagation (BP) neural network, PCA-RBF neural network is better in finger vein recognition. The result shows that PCA-RBF has faster training speed, simpler algorithm and higher recognition rate.

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Periodical:

Applied Mechanics and Materials (Volumes 325-326)

Pages:

1653-1658

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.325-326.1653

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Online since:

June 2013

Authors:

Cheng Bo Yu, Jun Tan, Lei Yu, Yin Li Tian

Keywords:

Dimensionality Reduction, Finger Vein Recognition, Principal Component Analysis (PCA), Radial Basis Function Neural Network

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