Guesmi, HaneneTrichili, HaneneAlimi, Adel M.Solaiman, BaselBrömme, ArslanBusch, Christoph2018-11-192018-11-192012978-3-88579-290-1https://dl.gi.de/handle/20.500.12116/18317The performance of the fingerprint identification process highly depends on its extractor of fingerprint features. So, to reduce the dimensionality of the fingerprint image and improve the identification rate, a fingerprint features extraction method based on Curvelet transform is proposed and presented in this paper. Thus, our paper focuses on presenting of our Curvelet-based fingerprint features extraction method. This method consists of two steps: decompose the fingerprint into set of sub-bands by the Curvelet transform and automatic extraction of the most discriminative statistical features of these sub-bands. An extensive experimental evaluation shows that the proposed method is effective and encouraging.enText/Conference Paper1617-5468