An efficient algorithm for fingerprint preprocessing and feature extraction

In practice, the placement of finger on the scanner for authentication is not done with the utmost care as when placed during the enrollment and this result in rejections of genuine users. Moreover, user behaviour and envionmental conditions decrease the geniune acceptance rate (GAR) for authentication of fingerprints. To overcome these limitations, an efficient preprocessing algorithm is proposed to achieve good vertical orientation and high ridge curvature area around the core point for fingerprint authentication and analysis. The algorithm is implemented in two stages. The process of obtaining the vertical oriented fingerprint image is carried out in the first step. This is followed by core point detection of a fingerprint. Core point detection is efficiently identified for any type of fingerprints. The developed algorithm is tested using a line based feature extraction algorithm with a large internal database and samples of fingerprint vericication competition (FVC). Only for the poor quality images, broken ridges are identified which results in a difference in minutiae points. With the proposed algorithm 94% of the tested images were oriented vertically and its genuiness is verified by comparing the minutiae details of the oriented and unoriented image of the same subject.