TRANSIENTLY CHAOTIC ASSOCIATIVE NETWORK FOR FINGERPRINT IMAGE ANALYSIS
This paper presents a new technique for fingerprint image matching in biometric security applications, based on the hybrid of Neural Network and Delaunay Triangulation methodology. The Delaunay triangulation of the minutiae set is transformed to a set of points in the discretized space using duality. This translation results in a sampling method be acquiring which the system tolerates displacement and noise of the input image. Finally, Transiently Chaotic Associative Network (TCAN) is used to learn the obtained pattern. Experimental results show a significant improvement in the False Rejection Rate over both the traditional Delaunay Triangulation based approach and direct Neural Network application.
fingerprint recognition chaotic neural networks delaunay tessellation