Estimating the Impact of Fingerprint Image Enhancement Algorithms for Better Minutia Detection

A very important step in automatic fingerprint recognition system is to automatically and reliably extract minutia from the input fingerprint images. But the performance of a minutia extraction algorithm relies heavily on the quality of the input fingerprint images and the image processing techniques used for enhancing the ridges and valleys of the fingerprint image and make the minutia distinguishable from the other parts of the fingerprint image. In this paper, we have evaluated three models of minutia detection systems which are particularly very much different in the way of enhancing the input image for minutia detection. It is proposed to use FFT and Gabor Filter based on frequency and orientation image enhancement technique instead of directional convolution and grey scale. Finally we have compared the performance of image enhancement algorithms using the number of minutia in all the three cases with the values of a human observer.