Artificial neural networks for finger vein recognition: A survey

Yimin Yin, Renye Zhang, Pengfei Liu, Wanxia Deng, Dayu Hu, Siliang He, Chen Li, Jinghua Zhang

Abstract: Finger vein recognition is an emerging biometric recognition technology. Different from the other biometric features on the body surface, the venous vascular tissue of the fingers is buried deep inside the skin. Due to this advantage, finger vein recognition is highly stable and private. Finger veins are virtually impossible to steal and difficult to interfere with by external conditions. Unlike the finger vein recognition methods based on traditional machine learning, the artificial neural network technique, especially deep learning, does not rely on feature engineering and has superior performance. To summarize the development of finger vein recognition based on artificial neural networks,this paper collects 174 related papers. First, we introduce the background of finger vein recognition and the motivation for this survey. Then, the development history of artificial neural networks and the representative networks on finger vein recognition tasks are introduced. The public datasets widely used in finger vein recognition are then described. After that, we summarize the related finger vein recognition tasks based on classical neural networks and deep neural networks, respectively. Finally, the challenges and potential development directions in finger vein recognition are discussed. This paper provides a comprehensive and novel summary of the application of artificial neural networks in the finger vein recognition field.

External IDs:dblp:journals/eaai/YinZLDHHLZ25