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Proceedings Paper

Development of neural network techniques for finger-vein pattern classification
Author(s): Jian-Da Wu; Chiung-Tsiung Liu; Yi-Jang Tsai; Jun-Ching Liu; Ya-Wen Chang
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Paper Abstract

A personal identification system using finger-vein patterns and neural network techniques is proposed in the present study. In the proposed system, the finger-vein patterns are captured by a device that can transmit near infrared through the finger and record the patterns for signal analysis and classification. The biometric system for verification consists of a combination of feature extraction using principal component analysis and pattern classification using both back-propagation network and adaptive neuro-fuzzy inference systems. Finger-vein features are first extracted by principal component analysis method to reduce the computational burden and removes noise residing in the discarded dimensions. The features are then used in pattern classification and identification. To verify the effect of the proposed adaptive neuro-fuzzy inference system in the pattern classification, the back-propagation network is compared with the proposed system. The experimental results indicated the proposed system using adaptive neuro-fuzzy inference system demonstrated a better performance than the back-propagation network for personal identification using the finger-vein patterns.

Paper Details

Date Published: 26 February 2010
PDF: 6 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75460F (26 February 2010); doi: 10.1117/12.852799
Show Author Affiliations
Jian-Da Wu, National Changhua Univ. of Education (Taiwan)
Chiung-Tsiung Liu, National Changhua Univ. of Education (Taiwan)
Yi-Jang Tsai, National Changhua Univ. of Education (Taiwan)
Jun-Ching Liu, National Changhua Univ. of Education (Taiwan)
Ya-Wen Chang, National Changhua Univ. of Education (Taiwan)

Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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