Fingerprint verification methods using delaunay triangulations

This paper presents a modification for robust minutiae based fingerprint verification methods that use Delaunay triangulations. The purpose of this modification is to decrease the number of comparison operations and the error rates within the matching process, by doing a full analysis of the Delaunay triangles. From this full analysis, a modified method was proposed. The identified minutiae represent nodes of a coZnnected graph composed of triangles. With this technique, the minimum angle over all triangulations is maximized, which gives local stability to the constructed structures against rotation and translation variations. Geometric thresholds and minutiae data were used to characterize the triangulations created from input and template fingerprint images. The effectiveness of the proposed modification is confirmed with calculations of False Acceptance Rate (FAR), False Rejected Rate (FRR) and Equal Error Rate (EER) over FVC2002 databases compared to other approaches results.