Fingerprint recognition using wavelet domain features

Image-based and minutiae-based are two major methods of fingerprint recognition. In this work, we presented an image-based fingerprint recognition method by using wavelet transformation and this method is efficient even for low quality fingerprint. The features extraction of the proposed method differing with previous wavelet methods is based on the blocks of enhanced region of interest (ROI). The alignment is required to build ROI including location the reference point and rotation alignment. Fingerprint matching was performed on simply Euclidian distance of feature vector extracted from wavelet domain. These features consist of mean energy, standard deviation and Shannon entropy for the purpose of making these features more discriminative. The good recognition accuracy was achieved on the FVC2002 database.