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26 February 2010 Development of neural network techniques for finger-vein pattern classification
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Proceedings Volume 7546, Second International Conference on Digital Image Processing; 75460F (2010) https://doi.org/10.1117/12.852799
Event: Second International Conference on Digital Image Processing, 2010, Singapore, Singapore
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.
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Jian-Da Wu, Chiung-Tsiung Liu, Yi-Jang Tsai, Jun-Ching Liu, and Ya-Wen Chang "Development of neural network techniques for finger-vein pattern classification", Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75460F (26 February 2010); https://doi.org/10.1117/12.852799
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