Journal of Pattern Recognition Research

Fingerprint has remained a very vital index for human recognition. In the field of security, series of Automatic Fingerprint Identification System (AFIS) have been developed. One of the indices for evaluating their contributions to the enforcement of security is the degree with which they appropriately verify or identify input fingerprints. This degree is generally determined by the quality of the fingerprint images and the efficiency of the algorithm. In this paper, a mathematical model for the fingerprint image enhancement is discussed and implemented. The mathematical model consists of different sub-models for the different levels of fingerprint enhancement which include segmentation, normalization, ridge orientation estimation, ridge frequency estimation, Gabor filter, binarization and thinning. The implementation of the model was carried out in an environment characterized by Window Vista Home Basic operating system as platform and Matrix Laboratory (MatLab) as frontend engine. Synthetic images as well as real fingerprints obtained from the manual method of ink and paper were used to test the adequacy of the different sub-models. The results show that each sub-model performs well with images with free or minimal noise level. The results also show the necessity of each level of the enhancement.
Keyword: AFIS, Pattern recognition, pattern matching, fingerprint, minutiae, image enhancement