Fast match-on-card technique using in-matcher clustering with ISO minutia template Online publication date: Fri, 31-Jul-2015
by Tai-Pang Chen; Wei-Yun Yau; Xudong Jiang
International Journal of Biometrics (IJBM), Vol. 7, No. 2, 2015
Abstract: Fingerprint match-on-card is receiving more attention from society because of higher level of security and less privacy concern. The ISO/IEC19794-2 for match-on-card defines the minutiae data format that contains the basic information. Therefore, match-on-card is a challenge, especially when dealing with deformation and common correspondence for alignment. In this paper, a novel in-matcher clustering method is proposed to search for the matched minutia clusters to cater for deformation. Moreover, a further matching step using Mahalanobis distance to measure the inter-cluster similarity is proposed to remove the wrongly matched clusters. Finally, the overall match score is generated by combining the scores from matched clusters and the geometrical structure of clusters. The proposed algorithm achieved an average EER ⇐ 5.1979% using all FVC databases. In the NIST evaluation, the achieved false match rate (FMR) = 0.001 and false non-match rate (FNMR) = 0.08 and the average on-card verification time is 1.01s using 8-bit smartcard.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Biometrics (IJBM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook