3d Finger Identification Using 3d Ridglet Neural Transformation


Abstract in English

This paper introduces, a proposed new identification method based on 3D Ridglet Transform. First phase, it considers the three dimensional fingerprint of human as a Personal Identification Number. Next, it produces the required features using the new proposed 3D Ridglet Transform. This transform is a generalization of adapted 2D Ridglet form. In the second phase we will consider the Back Propagation Neural Network authentication process, the evaluation tests of the proposed algorithm on a given database, for fifteen human Finger-Print, produce a perfect identification results (in comparison with [12]). Based on the evaluation test, we obtain that the authentication of the allowed Human Finger-Print on a noisy data, with a noise level up to 69% also with rotation of the input human Finger-Print up to 9 degree of rotation.

References used

Ramesh R. Galigekere, Ph.D, "New Algorithm for Image Analysis, Compression, and 2D Spectrum Estimation in the radon transform", department of electrical and computer Engineering, Concordia University-Montreal / Canada, 1997
Y. Shkolnisky, A. Averbuch, "3D Fourier Based Discrete Radon Transform", in Applied Computation Research Harmonic Analysis, 15 (2003) 33–69, 2003
Peter Toft, Ph.D thesis, "Radon Transform Theory and implementation", section digital signal processing-Technical University of Denmark, 1996

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