Chinese Optics Letters, 2010, 8 (6): 577, Published Online: Jun. 22, 2010   

Curvelet-based palm vein biometric recognition Download: 777次

Author Affiliations
College of Optoelectronic Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Abstract
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.

Qiang Li, Yan'an Zeng, Xiaojun Peng, Kuntao Yang. Curvelet-based palm vein biometric recognition[J]. Chinese Optics Letters, 2010, 8(6): 577.

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