Statistical Analysis of Fingerprint Pattern

Fingerprints are the ridge and furrow patterns on the tip of the finger and have been used extensively for personal identification of people. A number of approaches to fingerprint classification have been developed. Some of the earliest approaches did not make use of the rich information in the ridge structures and exclusively depended on the orientation field information.

Due to the limited amount of information present in the minutiae-based representation, it is desirable to explore alternative representations of fingerprints. To assess the performance limitations of popular minutiae-based fingerprint verification system, we theoretically estimate the probability of a false correspondence between two fingerprints from different fingers based on the minutiae representation of fingerprints. As a result, the most successful approaches need to use reliable structural/syntactic pattern recognition methods and statistical methods. This paper performs the comparison of a particular fingerprint configuration using different models. For a fair comparison, the differences between minutiae types are not considered.