Fingerprint identification algorithm based on delaunay triangulation and cylinder codes

Abstract

A new efficient fingerprint identification algorithm combining a modification of the Delaunay triangulation minutiae-based hashing technique for a model dataset, the Maltonian cylinder coding fingerprint matching method, and MAP-classifier learning procedure is proposed. Numerical experiments prove the robustness of the algorithm w.r.t. small perturbations of minutiae data and the sufficiently high level of natural noising for query fingerprints. Also, performance analysis results with comparison to state-of-the-art ‘Suprema’ identification algorithm are presented.