An Effective Method for Fingerprint Classification

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.

An Effective Fingerprint Classification and Search Method

This paper presents an effective fingerprint classification method designed based on a hierarchical agglomerative clustering technique. The performance of the technique was evaluated in terms of several real-life datasets and a significant improvement in reducing the misclassification error has been noticed. This paper also presents a query based faster fingerprint search method over the clustered fingerprint databases. The retrieval accuracy of the search method has been found effective in light of several real-life databases.