Novel Fingerprint Image Enhancement Algorithm

The purpose of this paper is to investigate the performance of a three-step procedure for the fingerprint identification and enhancement, using CLAHE (contrast limited adaptive histogram equalization) together with applying ´clip limit´, standard deviation analysis and sliding neighborhood as stages during processing of the fingerprint image. Firstly, CLAHE with clip limit is applied to enhance the contrast of the small tiles existing in the fingerprint image while using a bilinear interpolation to combine the neighboring tiles, eliminating the artificially induced boundaries. In a second step, the image is partitioned into an array of distinct blocks represented by matrices. Standard deviation of the matrix elements is calculated for each block and is used to remove the image background and obtain the boundaries for the region of interest. Finally, by using a slide neighborhood processing, an enhancement of the image is obtained by clarifying the Minutiae (endpoints and bifurcations) in each specific pixel, a process known as thinning. The paper presents the motivation for developing this method, its phases, and its possible advantages through a simulated investigation.