Intelligent fingerprint recognition system

Today, in the light of innovations in the field of biometrics, biometric images and processing of biomedical images have gained importance. Fingerprint recognition now works with the eye specialist to be produced in a laboratory environment. In literature, it is worked to minimize the margin of error in fingerprint identification. This study was done for the automatic fingerprint recognition. In here, Artificial Neural Networks (MANN) method is used as an alternative method for the automatic fingerprint recognition the multi-entropy. For this purpose, first, a fingerprint image database was composed. In preprocessing phase, center - the edges changing method is used for obtained variation of distance vector images. In feature extraction and classification phases, the norm, respectively, of the logarithmic energy and entropy threshold entropy value was calculated to be 3each of the images. Thus, feature vector is obtained and this feature vector are given to ANN classifier inputs in classification stage. Finally, in the testing phase, the ANN classifier of the correct classification performance and the success rate is calculated as the average rate was 85.06%.Keywords: Fingerprint recognition, fingerprint images, an artificial neural network, classifier, the concept of entropy, the center edge of change method.