Hand Vein Biometric Recognition Approaches Based on Wavelet, SVM, Articial Neural Network and Image Registration

Authors

  • Daniel Brito State University of Campinas (UNICAMP)
  • Lee Luan Ling State University of Campinas - UNICAMP

DOI:

https://doi.org/10.4114/intartif.vol22iss63pp101-120

Keywords:

Hand vein biometric, Support Vector Machine, Articial Neural Network, Image Registration, Wavelet.

Abstract

This paper describes in detail different hand vein recognition methods based on Wavelet-SVM, Wavelet-ANN and Image Registration. A new image segmentation and processing algorithm is proposed to efficiently locate vein regions and suitable for feature extraction (wavelet coefficients and normalized vein imagens) and classification (SVM, ANN and Image Registration). For real time recognition and high recognition rate, we proposed an integrated system which combines three above mentioned classification methods. The simulation results reveal that the proposed integrated system achieves 1% false rejection rate (FRR) and 0.02% false acceptance rate.

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Published

2019-02-27

How to Cite

Brito, D., & Ling, L. L. (2019). Hand Vein Biometric Recognition Approaches Based on Wavelet, SVM, Articial Neural Network and Image Registration. Inteligencia Artificial, 22(63), 101–120. https://doi.org/10.4114/intartif.vol22iss63pp101-120