Finger Vein Recognition Based on (2D)2 PCA and Metric Learning
Joint Authors
Yin, Yilong
Yang, Gongping
Xi, Xiaoming
Source
Journal of Biomedicine and Biotechnology
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-05-20
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers.
In this paper, (2D)2 PCA is applied to extract features of finger veins, based on which a new recognition method is proposed in conjunction with metric learning.
It learns a KNN classifier for each individual, which is different from the traditional methods where a fixed threshold is employed for all individuals.
Besides, the SMOTE technology is adopted to solve the class-imbalance problem.
Our experiments show that the proposed method is effective by achieving a recognition rate of 99.17%.
American Psychological Association (APA)
Yang, Gongping& Xi, Xiaoming& Yin, Yilong. 2012. Finger Vein Recognition Based on (2D)2 PCA and Metric Learning. Journal of Biomedicine and Biotechnology،Vol. 2012, no. 2012, pp.1-9.
https://search.emarefa.net/detail/BIM-463513
Modern Language Association (MLA)
Yang, Gongping…[et al.]. Finger Vein Recognition Based on (2D)2 PCA and Metric Learning. Journal of Biomedicine and Biotechnology No. 2012 (2012), pp.1-9.
https://search.emarefa.net/detail/BIM-463513
American Medical Association (AMA)
Yang, Gongping& Xi, Xiaoming& Yin, Yilong. Finger Vein Recognition Based on (2D)2 PCA and Metric Learning. Journal of Biomedicine and Biotechnology. 2012. Vol. 2012, no. 2012, pp.1-9.
https://search.emarefa.net/detail/BIM-463513
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-463513