Fingerprint verification using genetic algorithms

Fingerprint matching is still a challenging problem for reliable person authentication because of the complex distortions involved in two impressions of the same finger. In this paper, we propose a fingerprint matching approach based on Genetic Algorithms (GA), which finds the optimal global transformation between two different fingerprints. In order to deal with low quality fingerprint images, which introduce significant occlusion and clutter of minutiae features, we design the fitness function based on the local properties of each triplet of minutiae. The experimental results on National Institute of Standards and Technology fingerprint database, NIST-4, not only show that the proposed approach can achieve good performance even when a large portion of fingerprints in the database are of poor quality, but also show that the proposed approach is better than another approach, which is based on mean-squared error estimation.