Classification of Extended Delaunay Triangulation for Fingerprint Indexing

Abstract

In this paper, we propose an efficient indexing mechanism for the fingerprints based on minutiae triplets. First, we compute the Delaunay triangulation for each fingerprint using the minutiae features. Further, we define a novel representation for the fingerprint named extended triangle set, which is very tolerant to missing minutiae. The defined extended triangle set is an extension of the Delaunay triangulation and is used in combination with a classification approach to narrow down the search space of a fingerprint database. Experiments are conducted on different Fingerprint Verification Competition (FVC) databases and the results show that, while maintaining high hit rate the proposed method achieves lower penetration rate than existing methods.