基于视频的掌纹掌脉联合识别系统

Palm Print and Palm Vein Joint Recognition System Based Video

搭建了基于视频的掌纹掌脉联合识别系统。首先对掌纹掌脉采用新的注册和识别方式,用系统获取的手掌运动视频来代替传统采集方式所获取的静态图像,认证时手掌无需刻意停留,只需横扫而过,有效地增强了认证的亲和性。提出了将旋转视频和横扫视频进行融合注册的新策略,从而确保了注册特征的丰富性和完整性,增强了系统对不同认证姿态的稳健性。为了提升已注册用户的识别速度,提出一种级联融合策略来进行识别。构建了一个包含100个手掌、1200段带有运动模糊的掌纹掌脉视频数据库,并在数据库上进行了大量仿真,结果显示新系统在915ms的期望耗时内能够达到1.51%的等误率,验证了所构建新系统的有效性和实用性。

A novel palm print and palm vein joint recognition system based video is built.First of all,a novel registration and identification approach is proposed,and we can obtain the palm motion video by proposed system instead of static image obtained by traditional collection method.The approach allows the users simply sweep their palms across the acquisition platform without having to stop, which effectively enhances the affinity of authentication.A new strategy of fusing rotating videos with sweep videos to generate the registration feature set is proposed,which ensures the abundance and integrality of the register feature and enhances the robustness of the system for various palm postures in authentication.A cascaded fusion strategy is presented to improve the recognition speed of the registered users.We construct a palm print and palm vein database containing 1200 videos with motion blur from 100 palms and carry out a series simulations.The results show that the proposed system can achieve a low equal error rate of 1.51% within the expected time consumption of 915 ms,which desmonstrates the effectiveness and practicality of the new system.