A cost-effective fingerprint recognition system for use with low-quality prints and damaged fingertips

摘要

The development of a robust algorithm allowing good recognition of low-quality fingerprints with inexpensive hardware is investigated. A threshold FFT approach is developed to simultaneously smooth and enhance poor quality images derived from a database of imperfect prints. Features are extracted from the enhanced images using a number of approaches including a novel wedge ring overlay minutia detector that is particularly robust to imperfections. Finally, a number of neural net and statistically based classifiers are evaluated for the recognition task. Results for various combinations of the process are presented and discussed with regard to their utility in such a system.