A hidden Markov model fingerprint classifier

Fingerprint classification is an important indexing method for any fingerprint database or recognition system. Fingerprints are classified based on overall characteristics. This paper describes a novel method of classification using hidden Markov models to recognize the ridge structure of the print. The paper also describes a method for achieving any level of accuracy required by the system by sacrificing the efficiency of the classifier. Results are presented on a NIST fingerprint database.