A methodology for identification of fingerprints based on Gabor filter

This work presents an automatic fingerprint identification system using a coefficient map in the power spectrum based on Gabor filter. This filter was created by Dennis Gabor in 1946 and is being used in many biometric technologies. The fingerprint core is found by pixel neighborhood technique. Around the core, the input image is divided in quadrants where information about texture orientation in three different Gabor filter directions is extracted. The angles used are 0, 45 and 90 degrees. It is accomplished convolutions among such Gabor filter orientations with each quadrant of the input image through the Fast Fourier Transform routine. After that, it is needed to identify the image in the frequency domain and the power spectrum is done. The maximum coefficient of the power spectrum is found and a map of forty coefficients is created around this maximum coefficient. That map is summed and divided by the maximum coefficient. Each result is an identifier of the image. Accomplishing such method using three Gabor filter orientations convoluted with the quadrants of the input image results in twelve identifiers. Those twelve identifiers are compared in the matching process. Experimental results demonstrate the good efficiency of the methodology for fingerprint images of good quality.