Kekre´s transform for protecting fingerprint template

In this paper, Kekre´s transform is proposed for protecting fingerprint template and a symmetric bio-hash function is used to improve the protection of the fingerprint biometric template. In the proposed approach; firstly the principal curve approach is used to extract the features from the fingerprint template. Then, we applied a transformation phase using Kekre´s transform. It starts by calculating the row and the column mean vectors of fingerprint image to get Kekre transform feature vectors. Finally, we adapt the bio-hash function to calculate the translation, rotation, and the error rate to increase the security performance. Experiments using well know benchmark CASIA fingerprint-V5 data sets show that the obtained results proved that the kekre transform approach is more efficient compared to class distribution preserving (CDP) approach and the error rate is minimized by %20.