By Topic

Refining Local 3D Feature Matching through Geometric Consistency for Robust Biometric Recognition

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Islam, S.M.S. ; Sch. of Comput. Sci. & Software Eng., Univ. of Western Australia, Crawley, WA, Australia ; Davies, R.

Local features are gaining popularity due to their robustness to occlusion and other variations such as minor deformation. However, using local features for recognition of biometric traits, which are generally highly similar, can produce large numbers of false matches. To increase recognition performance, we propose to eliminate some incorrect matches using a simple form geometric consistency, and some associated similarity measures. The performance of the approach is evaluated on different datasets and compared with some previous approaches. We obtain an improvement from 81.60% to 92.77% in rank-1 ear identification on the University of Notre Dame Biometric Database, the largest publicly available profile database from the University of Notre Dame with 415 subjects.

Published in:

Digital Image Computing: Techniques and Applications, 2009. DICTA '09.

Date of Conference:

1-3 Dec. 2009