基于正态分布变换的多位姿手掌部三维静脉识别

研究基于三维点云匹配的多位姿手部静脉识别.考虑手部静脉点云的特点，结合双目视觉原理，建立了一种结合三维特征阵列和静脉点云的扩展数据库，提出了一种基于三维特征阵列的静脉点云粗配准算法.在双目静脉图像中提取稳定特征并重建为三维特征，根据三维特征匹配结果初步消除静脉点云位姿差异.并采用改进的正态分布变换算法完成静脉点云匹配.实验表明，本文算法能够有效提高多位姿下的静脉点云识别率，即使手部位姿变化范围较大时，系统的识别率仍超过90%. 

3D Hand Vein Recognition Based on Normal Distribution Transform for Multi-Pose Authentication

A multi-pose hand vein recognition algorithm was proposed based on 3D point cloud matching. Considering the characteristics of hand vein point cloud,an extended database that combines 3D feature arrays and vein point cloud data was established according to stereo vision principle. A 3D feature array based calculation method was proposed for coarse point cloud registration. In stereo vein image, the stable feature points were extracted and reconstructed to three-dimensional features. The posture difference of hand vein point clouds was eliminated according to the result of 3D feature matching. An improved normal distribution transform algorithm was used to complete the vein point cloud matching. Experiment results show that the proposed algorithm can effectively improve the recognition rate under multi-pose. The recognition rate of the system can be more than 90%, even if the hand posture changes in a large range.