Fingerprint recognition for varied degrees of image distortion using three-rate hybrid Kohonen neural network

One of the most difficult problems in fingerprint recognition has been that the recognition performance is significantly influenced by distorted fingertip surface condition, which may vary depending on environmental or personal causes. Addressing this problem, this paper presents the three-rate hybrid Kohonen neural network (TRHKNN) for distorted fingerprint image processing in conditions of wide variation in degree of distortion. This TRHKNN consists of ldquofastrdquo Kohonen neural network (FKNN), ldquomiddlerdquo Kohonen neural network (MKNN) and ldquoslowrdquo Kohonen neural network (SKNN). The received TRHKNN has not only high speed of image recognition, but also high speed of image restoration. This approach demonstrates that the proposed TRHKNN is capable not only to identify the distorted image of fingerprint but also to restore the undistorted image of fingerprint. These examples with simulations by MATLAB/Simulink environment show the computing procedure and applicability of TRHKNN for fast-acting fingerprint image recognition in distorted fingertip surface conditions.