Representation of fingerprint recognition system based on geometric and statistical features of distance and angle of minutiae points.

This paper presents an approach for identifying fingerprints through the extraction of geometric and statistical features of characteristic Minutiae. The proposed approach is in accordance with statistical features to extract important points from the skeleton of a fingerprint's image. Through the addition of geometric features as a kind of preprocessing to this approach, the images are divided into distinct regions. In this approach, statistical parameters like min, max, mean and standard deviation are applied in order to compute the general abstract of the features. Another achievement in this article is the presentation of a similarity measure in identification tools which is only used for methods based on matching patterns. The Optimized version of the proposed method achieved near zero EER percentage in some of the datasets. [ABSTRACT FROM AUTHOR]