Various Mathematical and Geometrical Models for Fingerprints: A Survey

Abstract

Abstract- Fingerprints are the most universal, unique and persistent biometrics. The growing interest and eventually the need for advanced security, privacy and user convenience has put an access to fingerprint recognition, beyond the other biometrics recognition systems. Despite the ingenious methods improvised to increase the efficiency of detection in growing identity frauds, the growing demands for fingerprint as a biometric recognition system has quickly become overwhelming. Major challenges coming in the way of a robust fingerprint recognition system are the presence of noise, cuts, wet or dry images, different pressure and skin conditions, etc. The main objective of this paper is to review the extensive research on fingerprint recognition over the last decades and to address the present challenges. A comprehensive analysis can be made from the tabular form of the presented summary table using various techniques and features. Finally, the future directions of fingerprint recognition are explored. extraction, comparison and matching. Image enhancement belongs to preprocessing. Image enhancement is done to improve the image quality by a fingerprint recognition system [6]. Next block is feature extraction, where different features are extracted for comparison and matching [7], [8]. Next block is for comparing the extracted feature with the previous data stored in the database [9]. The last and the final stage is matching or indexing, which is done either by classification or matching [10]. Fingerprint classification and indexing techniques speed up the search in fingerprint based identification systems.. The current state of the art algorithms for fingerprint matching are too expensive [11]