Hand veins feature extraction based on morphology and Cellular Neural Network

Abstract

Vein pattern recognition is an emerging contactless near infrared biometric technology. It has drawn wide attention in recent years. A fingerprint-based identification system using Cellular Neural Networks has already been proposed. Discrete-time Cellular Neural Network (DT-CNN) is introduced into binary morphology owing to the natural corresponding relationship between them, and then the morphology operation is transformed into multi-layer DT-CNN under some specific template. Multi-layer DT-CNN is transformed into Monolayer DT-CNN by optimizing design to reduce the complexity of the operation. The method has a better performance and converges quickly.