Personal authentication using hand vein and knuckle shape point cloud matching

Qishen Zhang, Ya Zhou, Danting Wang, Xiaoming Hu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Citations (Scopus)

Abstract

This paper presents a new approach to authenticate individuals using hand vein point cloud matching with the help of a hardware system. The 3D point clouds of hand veins and knuckle shape were obtained by a binocular stereoscopic vision device. Edges of the hand veins and knuckle shape are used as key-points instead of other feature descriptors because they are better representing the spatial structure of hand vein patterns and significantly increasing the amount of key-points. A kernel correlation analysis approach, which has high sensitivity in hand vein spatial point clouds recognition and doesn't need pre-training the classifier, is proposed to register the 3D point clouds. A hand vein point clouds dataset contains 18 persons' information has been established. The experimental authentication result based on the dataset shows that the method works well and the algorithm is less time-consuming compared with 2D image matching strategies.

Original languageEnglish
Title of host publicationIEEE 6th International Conference on Biometrics
Subtitle of host publicationTheory, Applications and Systems, BTAS 2013
PublisherIEEE Computer Society
ISBN (Print)9781479905270
DOIs
Publication statusPublished - 2013
Event6th IEEE International Conference on Biometrics: Theory, Applications and Systems, BTAS 2013 - Washington, DC, United States
Duration: 29 Sept 20132 Oct 2013

Publication series

NameIEEE 6th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2013

Conference

Conference6th IEEE International Conference on Biometrics: Theory, Applications and Systems, BTAS 2013
Country/TerritoryUnited States
CityWashington, DC
Period29/09/132/10/13

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