A Small Scale Fingerprint Matching Scheme Using Digital Curvelet Transform

This paper proposes a new method for fingerprint matching based on the features extracted using a new multiresolution analysis tool called Digital Curvelet Transform. The curvelet coefficients extracted from enhanced fingerprint images act as the feature-set for a k-nearest neighbor classifier. The performance of this scheme has been evaluated on a small database of 120 images. A comparative study between the wavelet-based and the curvelet-based techniques has also been included. The high recognition rate achieved by using this method suggests an efficient solution for a small scale fingerprint recognition system. Note that, this paper is the first documented attempt to explore the possibilities of a new multiresolution analysis tool called curvelet transform to address the problem of fingerprint identification.