Curvelet-based palm vein biometric recognition

<正>A novel personal recognition system utilizing palm vein patterns and a novel technique to analyze these vein patterns is presented.The technique utilizes the curvelet transform to extract features from vein patterns to facilitate recognition.This technique provides optimally sparse representations of objects along the edges.Principal component analysis(PCA) is applied on curvelet-decomposed images for dimensionality reduction.A simple distance-based classifier,such as the nearest-neighbor(NN) classifier,is employed. The experiments are performed using our palm vein database.Experimental results show that the algorithm reaches a recognition accuracy of 99.6%on the database of 500 distinct subjects.     

双多通道虹膜识别系统的研究

在双多通道虹膜识别系统中,研究了局部区域通道对识别率的影响,提出了双向式区域划分和通道数的优化。研究了小波滤波器通道对识别能力的影响和滤波器通道的选择,给出了引入小波包通道来提升识别率的新方法。通过对WED(Weighted Euclidean Distance)分类器的改进研究,提出了相对WED分类器的新概念,进一步提高了系统的识别能力。