Abstract
In this paper, an effective fingerprint verification method for varying qualities of fingerprint images is described. When an optical sensor is used for imaging a fingerprint, the image quality is degraded especially due to a lack of moisture on the finger surface. Under such a condition, the captured fingerprint images are often faded. First, we investigated a method for improving the quality of faded fingerprint images, which is based on high frequency emphasis of the image using Fourier transformation. After the image is enhanced, the peaks of the group delay spectra (GDS) which are the features extracted for verification are more distinct than those extracted from the original image. When the reference patterns are selected from the fingerprint data obtained in April, the verification rate with the high frequency emphasis is 90.8%, while the rate without the emphasis is 75.3%. However, for the data obtained in February which include many faded fingerprints, the verification rate strongly decreases. Second, we examined a method to adapt differences in seasonally dependent image quality based on updating a reference pattern in terms of the accepted input pattern. Using this method, when the reference patterns are composed of the February data, the verification rate is improved from 57.1% to 85.2%. Furthermore, by resetting the verification threshold value whenever a reference pattern is updated, the rate increases to 96.5%, which is equivalent to that when the all seasonal data are registered.
