A New Approach for the Fingerprint Classification Based On Gray-Level Co- Occurrence Matrix

In this paper, we propose an approach for the classification of fingerprint databases. It is based on the fact that a fingerprint image is composed of regular texture regions that can be successfully represented by co-occurrence matrices. So, we first extract the features based on certain characteristics of the cooccurrence matrix and then we use these features to train a neural network for classifying fingerprints into four common classes. The obtained results compared with the existing approaches demonstrate the superior performance of our proposed approach. Keywords—Biometrics, fingerprint classification, gray level cooccurrence matrix, regular texture representation.