Fingerprint Recognition Algorithms for Partial and Full Fingerprints

An urgent need to develop accurate biometric recognition system is expressed by governmental agencies at the local, state, and federal levels, as well as by private commercial companies. Fingerprinting is the most practical and widely used biometric technique. The pattern of ridges and valleys of each fingerprint is unique. The minutiae based algorithm is widely used for fingerprint authentication. One of the significant parts of this algorithm is the classification of fingerprints which allows minimizing significantly the number of fingerprints referenced for each identification procedure. However, the minutiae algorithm has some serious drawbacks. If the core of a fingerprint is not visible, then identification cannot proceed. Yet in some cases, partial fingerprints need to be identified. We recently developed a novel contactless line scanner for recognition of fingerprint pattern that converts a three dimensional object like a finger into a two dimensional image with minimal distortion. This novel imaging technique based on a line by line scanned image required the development of a new recognition algorithm. In this study, we propose two new algorithms. The first algorithm, called the spaced frequency transformation algorithm (SFTA), is based on taking the fast Fourier transform of the images. The second algorithm, called the line scan algorithm (LSA), was developed to compare partial fingerprints and reduce the time taken to compare full fingerprints. A combination of SFTA and LSA provides a very efficient recognition technique.