Palm vein recognition method based on fusion of local Gabor histograms

doi:10.1016/S1005-8885(17)60242-5

中国邮电高校学报(英文) ›› 2017, Vol. 24 ›› Issue (6): 55-66.doi: 10.1016/S1005-8885(17)60242-5

• Artificial Intelligence • 上一篇下一篇

Palm vein recognition method based on fusion of local Gabor histograms

马欣¹,景晓军²

1. 北京邮电大学
2. 北京邮电大学研究生院信息与通信学院

收稿日期:2017-07-03 修回日期:2017-09-28 出版日期:2017-12-30 发布日期:2017-12-01
通讯作者: 马欣 E-mail:xinma@bupt.edu.cn
基金资助:
the CASIA-MS-PalmprintV1 database provided by the CASIA in this research.

Palm vein recognition method based on fusion of local Gabor histograms

马欣1,景晓军2

1. 北京邮电大学 2. 北京邮电大学研究生院信息与通信学院

Received:2017-07-03 Revised:2017-09-28 Online:2017-12-30 Published:2017-12-01
Contact: Xin MA E-mail:xinma@bupt.edu.cn
Supported by:
the CASIA-MS-PalmprintV1 database provided by the CASIA in this research.

摘要/Abstract

摘要： Gabor features have been shown to be effective for palm vein recognition. This paper presents a novel feature representation method, implementing the fusion of local Gabor histograms (FLGH), in order to improve the accuracy of palm vein recognition systems. A new local descriptor called local Gabor principal differences patterns (LGPDP) encodes the Gabor magnitude using the local maximum difference (LMD) operator. The corresponding Gabor phase patterns are encoded by local Gabor exclusive OR (XOR) patterns (LGXP). Fisher’s linear discriminant (FLD) method is then implemented to reduce the dimensionality of the feature representation. Low-dimensional Gabor magnitude and phase feature vectors are finally fused to enhance accuracy. Experimental results from Institute of Automation, Chinese Academy of sciences (CASIA) database show that the proposed FLGH method achieves better performance by utilizing score-level fusion. The equal error rate (EER) is 0.08%, which outperforms other conventional palm vein recognition methods (EER range from 2.87% to 0.16%), e.g., the Laplacian palm, minutiae feature, Hessian phase, Eigenvein, local invariant features, mutual foreground local binary patterns (LBP), and multi-sampling feature fusion methods.

关键词: palm vein recognition, Gabor filter, local histogram, Fisher’s linear discriminant

Abstract: Gabor features have been shown to be effective for palm vein recognition. This paper presents a novel feature representation method, implementing the fusion of local Gabor histograms (FLGH), in order to improve the accuracy of palm vein recognition systems. A new local descriptor called local Gabor principal differences patterns (LGPDP) encodes the Gabor magnitude using the local maximum difference (LMD) operator. The corresponding Gabor phase patterns are encoded by local Gabor exclusive OR (XOR) patterns (LGXP). Fisher’s linear discriminant (FLD) method is then implemented to reduce the dimensionality of the feature representation. Low-dimensional Gabor magnitude and phase feature vectors are finally fused to enhance accuracy. Experimental results from Institute of Automation, Chinese Academy of sciences (CASIA) database show that the proposed FLGH method achieves better performance by utilizing score-level fusion. The equal error rate (EER) is 0.08%, which outperforms other conventional palm vein recognition methods (EER range from 2.87% to 0.16%), e.g., the Laplacian palm, minutiae feature, Hessian phase, Eigenvein, local invariant features, mutual foreground local binary patterns (LBP), and multi-sampling feature fusion methods.

Key words: palm vein recognition, Gabor filter, local histogram, Fisher’s linear discriminant

Ma Xin,Jing Xiaojun. Palm vein recognition method based on fusion of local Gabor histograms[J]. JOURNAL OF CHINA UNIVERSITIES OF POSTS AND TELECOM, 2017, 24(6): 55-66.

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Palm vein recognition method based on fusion of local Gabor histograms

Palm vein recognition method based on fusion of local Gabor histograms

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