An Effective Method for Fingerprint Classification

Abstract EN

This paper presents an effective method for fingerprint classification using data mining approach.

Initially, it generates a numeric code sequence for each fingerprint image based on the ridge flow patterns.

Then for each class, a seed is selected by using a frequent itemsets generation technique.

These seeds are subsequently used for clustering the fingerprint images.

The proposed method was tested and evaluated in terms of several real-life datasets and a significant improvement in reducing the misclassification errors has been noticed in comparison to its other counterparts.