Combining Gabor filter and FFT for fingerprint enhancement based on a regional adaption method and automatic segmentation

Abstract

Fingerprints are the best biometric identity mark due to the consistency during life time and uniqueness. To increase the classification accuracy of fingerprint images, it is necessary to improve image quality which is a key role for correct recognition. In other words, enhancing the fingerprint images leads us to obtain better results in classification of fingerprint images. Although Gabor filter and fast Fourier transform (FFT) are used to enhance fingerprint images, Gabor filter acts better than FFT in detection of incorrect ridge endings and ridge bifurcation, while FFT tries to connect broken ridges together and fill the created holes. This paper tries to enhance gray-scale fingerprint images by combining the Gabor filter and FFT in order to get benefit from the advantages of each enhancing filter (Gabor filter and FFT). A method is proposed for fingerprint image segmentation based on the image histogram and density. By employing the proposed method which enhances the fingerprint images using the better enhancing filter in each part, the experimental results show that the whole finger print is better enhanced, and consequently, it leads to a better recognition rate.