@inproceedings{1ccf88cca3d84126b769803d05315d2c,
title = "Finger vein recognition using LBP variance with global matching",
abstract = "Finger vein recognition has been identified as a stable biometrics technique that has many advantages as compared to other techniques. The biggest challenge that is faced while using this technique is to make the features rotarionally invariant. In this paper, local binary pattern variance (LBPV) is proposed to address this challenge and to characterize the local contrast information into the one-dimensional LBP histogram. Global matching method is used to further quicken the matching scheme and to reduce feature dimensions using distance measurement resulting to minimal computational cost. The classification rate of this method is tested using support vector machine (SVM), which gives it a high classification rate.",
keywords = "Biometrics, Feature extraction, Finger vein, LBPV, global matching, rotational invariance",
author = "Wang, \{Kuan Quan\} and Khisa, \{Anne S.\} and Wu, \{Xiang Qian\} and Zhao, \{Qiu Shi\}",
year = "2012",
doi = "10.1109/ICWAPR.2012.6294778",
language = "英语",
isbn = "9781467315326",
series = "International Conference on Wavelet Analysis and Pattern Recognition",
pages = "196--200",
booktitle = "Proceedings of 2012 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2012",
note = "2012 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2012 ; Conference date: 15-07-2012 Through 17-07-2012",
}