Development of neural network techniques for finger-vein pattern classification

Jian-Da Wu, Chiung Tsiung Liu, Yi Jang Tsai, Jun Ching Liu, Ya Wen Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


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.

Original languageEnglish
Title of host publication2nd International Conference on Digital Image Processing
Publication statusPublished - 2010 Mar 22
Event2nd International Conference on Digital Image Processing - Singapore, Singapore
Duration: 2010 Feb 262010 Feb 28


Other2nd International Conference on Digital Image Processing

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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