@inproceedings{fe9decb989a548e4b1f73f98446dad4d,
title = "Hand vein recognition based on orientation of LBP",
abstract = "Vein recognition is becoming an effective method for personal recognition. Vein patterns lie under the skin surface of human body, and hence provide higher reliability than other biometric traits and hard to be damaged or faked. This paper proposes a novel vein feature representation method call orientation of local binary pattern (OLBP) which is an extension of local binary pattern (LBP). OLBP can represent the orientation information of the vein pixel which is an important characteristic of vein patterns. Moreover, the OLBP can also indicate on which side of the vein centerline the pixel locates. The OLBP feature maps are encoded by 4-bit binary values and an orientation distance is developed for efficient feature matching. Based on OLBP feature representation, we construct a hand vein recognition system employing multiple hand vein patterns include palm vein, dorsal vein, and three finger veins (index, middle, and ring finger). The experimental results on a large database demonstrate the effectiveness of the proposed approach.",
keywords = "Gaussian matched filter, Hand vein, Local binary pattern, Orientation of lbp, Support vector machine",
author = "Wei Bu and Xiangqian Wu and Enying Gao",
year = "2012",
doi = "10.1117/12.919637",
language = "英语",
isbn = "9780819490490",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring II; and Biometric Technology for Human Identification IX",
note = "Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring II; and Biometric Technology for Human Identification IX ; Conference date: 23-04-2012 Through 25-04-2012",
}