ALGORITHMS FOR FINGERPRINT CLASSIFICATION

Аннотация

Currently, biometric methods of personality are becoming more and more relevant recognition
technology. The advantage of biometric identification systems, in comparison with traditional approaches, lies in the
fact that not an external object belonging to a person is identified, but the person himself. The most widespread
technology of personal identification by fingerprints, which is based on the uniqueness for each person of the pattern
of papillary patterns. In recent years, many algorithms and models have appeared to improve the accuracy of the
recognition system. The modern algorithms (methods) for the classification of fingerprints are analyzed. Algorithms
for the classification of fingerprint images by the types of fingerprints based on the Gabor filter, wavelet - Haar,
Daubechies transforms and multilayer neural network are proposed. Numerical and results of the proposed
experiments of algorithms are carried out. It is shown that the use of an algorithm based on the combined application
of the Gabor filter, a five-level wavelet-Daubechies transform and a multilayer neural network makes it possible to
effectively classify fingerprints.