NDLI: Finger-vein authentication based on deformation-tolerant feature-point matching

Content Provider	Springer Nature Link
Author	Matsuda, Yusuke Miura, Naoto Nagasaka, Akio Kiyomizu, Harumi Miyatake, Takafumi
Copyright Year	2016
Abstract	A novel method for finger-vein authentication based on feature-point matching is proposed and evaluated. A finger-vein image captured by infrared light contains artifacts such as irregular shading and vein posture deformation that can degrade accuracy of finger-vein authentication. Therefore, a method is proposed for extracting features from vein patterns and for matching feature points that is robust against irregular shading and vein deformation. In the proposed method, curvature of image-intensity profiles is used for feature point extraction because such image profiles are a robust feature against irregular shading. To increase the number of feature points, these points are extracted from any positions where vein shape is non-linear. Moreover, a finger-shape model and non-rigid registration method are proposed. Both the model and the registration method correct a deformation caused by the finger-posture change. It is experimentally shown that the proposed method achieves more robust matching than conventional methods. Furthermore, experiments on finger-vein identification show that the proposed method provides higher identification accuracy than conventional methods.
Starting Page	237
Ending Page	250
Page Count	14
File Format	PDF
ISSN	09328092
Journal	Machine Vision and Applications
Volume Number	27
Issue Number	2
e-ISSN	14321769
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2016-01-22
Publisher Place	Berlin/Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Biometrics Finger-vein authentication Feature-point matching Irregular shading Correction of deformation Pattern Recognition Image Processing and Computer Vision Communications Engineering, Networks
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Computer Science Applications Software Hardware and Architecture

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