Altun, Adem AlpaslanAllahverdi, NovruzKoçer, Hasan ErdinçYılmaz, T.Alan, Selahattin2020-03-262020-03-2620050780392396; 9780780392397https://dx.doi.org/10.1109/SIU.2005.1567662https://hdl.handle.net/20.500.12395/19980IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005 -- 16 May 2005 through 18 May 2005 -- Kayseri -- 69003Minutiae extraction is one of the most important steps for automatic fingerprint identification and classification systems. The performance of minutiae extraction can be changed depends on an image enhancement algorithm. Minutiaes of the fingerprint are local discontinuities in the fingerprint pattern as terminations and bifurcations. In this work, we propose two methods for fingerprint image enhancement. The first one is carried out using local histogram equalization, noise reduction filters, and image binarization. In noise reduction step, linear, median and wiener filters are used. The results are compared with each other with regard to performance. In the second method a contourlet transform is applied. Contourlet transform is a new extension of the wavelet transform in two dimensions using multiscale and directional filter banks for direct grayscale enhancement. The results achieved from this method are compared with those obtained from wavelet transform. Both methods mentioned above are increase the efficiency of minutiae extraction with regard to minutiae specification and process time. ©2005 IEEE.tr10.1109/SIU.2005.1567662info:eu-repo/semantics/closedAccessConference Object2005229232N/A