弱约束条件下多特征融合的手背静脉识别关键算法研究

Research on Key Algorithms of Dorsal Hand Vein Recognition Based on Multi-feature Fusion Under Weak Constraint Conditions

随着信息采集、存储和处理技术的不断更新,基于手背静脉特征的身份识别技术成了生物识别研究领域的热点。本文研究了静脉图像预处理、静脉图像分割、静脉特征提取以及静脉特征匹配的过程,重点是在弱约束条件下,通过对静脉识别过程中静脉图像分割、静脉特征提取等关键算法的研究,提高了静脉特征的稳健性和高可区分性,获得了较理想的静脉特征匹配识别率。

With the continuous updating of information collection,storage and processing technology,the identification technology based on the dorsal hand vein features has become a hotspot in the field of biometrics.This paper studies the processes of vein image preprocessing,vein image segmentation,vein feature extraction and vein feature matching.The emphasis is to improve the robustness and high distinguishability of vein features by studying the key algorithms such as vein image segmentation and vein feature extraction in the process of vein recognition under weak constraints,and obtain an ideal vein feature matching recognition rate.