Hand veins feature extraction based on morphology and Cellular Neural Network

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.