Fingerprint classification based on multiple discriminant analysis

In this paper an effective fingerprint classification method based on Multiple Discriminant Analysis (MDA) is presented. The typology information is used to classify fingerprints. We also describe a feature extraction method based on Gabor filters. The effectiveness of our method is based on matters, that a reference point is searched from the region of interest and after finding the reference point, we crop the smaller image below the reference point. Then every operation, like feature calculation, is done only to this smaller image. The method was tested using artificially generated fingerprint database. With a uniform fingerprint distribution our classifier works an accuracy of 95.8% for the five-class problem.