Search

We introduce a hybrid fingerprint recognition method built from minutiae and quaternion orthogonal moments. The proposed algorithm includes four steps: extraction of the minutiae triplets (m-triplets), first pass of triplets minutiae matching, validation step of these triplets by characterizing their neighboring gray-level image information through feature vectors of quaternion radial moments, and an adequate similarity measure. By boosting the local minutiae matching step, we avoid consolidation and global matching. To show the added-value of our method, several algorithms for extracting and matching m-triplets are considered and an experimental comparison is established. Experiments are carried out using all four parts of the FVC2004 dataset. Results indicate that the combination of the geometrical features and the quaternion radial moments of the m-triplets leads to an improvement in the overall fingerprint matching performance and demonstrate the expected gain of integrating a validation step in an m-triplets based fingerprint matching algorithm. [ABSTRACT FROM AUTHOR]