Omni-direction Palm Vein Recognition Technology with Multi-Dimensional Image Quality Feedback Network

Abstract

The advantages of non-contact and embedded palm vein recognition technology in terms of security, privacy, and convenience are highlighted. Performance factors include error rate, rejection rate, and real-time processing, while engineering factors include small size, scalability, and cost-effectiveness. However, the non-contact sampling mode is susceptible to uncontrollable factors such as palm placement and posture, as well as external environmental influences like complex backgrounds and strong lighting. This paper proposes an omni-direction palm vein recognition (oPVR) method that integrates geometric and brightness multi-dimensional image quality feedback (MIQF), including integrity judgment, scale assessment, rotation angle detection. The method involves hand detection network, palm single-shot multibox detection (P-SSD) network for region of interest(ROI), and vein feature extraction network. These enhancements effectively improve recognition performance under environmental disturbances and pose variations. Based on a real-world database and a real-time demonstration system, a series of comparative tests and ablation experiments were conducted to validate the algorithm's accuracy, speed and usability for large-scale applications.