Altun, Adem AlpaslanAllahverdi, Novruz2020-03-262020-03-262007978-3-540-71590-00302-97431611-3349https://hdl.handle.net/20.500.12395/214878th International Conference on Adaptive and Natural Computing Algorithms (ICANNGA) -- APR 11-14, 2007 -- Warsaw Univ Technol, Warsaw, POLANDIn order to ensure that the performance of a fingerprint recognition system will be powerful with respect to the quality of input fingerprint images, the enhancement of fingerprints is essential. In this study wavelet transform and contourlet transform which is a new extension of the wavelet transform in two dimensions are applied for fingerprint enhancement. In addition, feature selection is a process that chooses a subset of features from the original fingerprint features so that the feature space is optimally reduced according to a certain criterion. In this study, a Genetic Algorithms (GAs) approach to fingerprint feature selection is proposed and selected features are input to Artificial Neural Networks (ANNs) for fingerprint recognition. The performance has been tested on fingerprint recognition.eninfo:eu-repo/semantics/closedAccessConference Object4432467+Q3WOS:000246098200053N/A