Abstract
This paper presents a method of automatic recognition of fingerprint diffraction images of motor vehicle users. The proposed method is based on the basic physical properties of the Fourier transform. It creates the possibility of reducing the problem of recognition to the Fourier transform of the image function, extraction of characteristic features vector and classification of input images.
Highlights
The Automatic Target Recognition from images (ATR) is one of the major contemporary research problems [1-11]
The goal of the following experiment is: - determining whether classification of fingerprints by the neural network is possible, - determining the quality of classification by the optoelectronic system (RWD + Artificial Neural Network (ANN)), - determining the advantages of classification using spectral power density (are these signals only from rings or only wedges or from wedges and rings), which are obtained from the extractor of characteristic features in the form of Ring-Wedge Detector (RWD)
Methods based on neural networks of characteristic features classification may be useful in this problem
Summary
The Automatic Target Recognition from images (ATR) is one of the major contemporary research problems [1-11]. Many researchers and companies are trying to build a system that is both reliable, fast and adaptable. Hybrid (optoelectronic) solutions play a significant role among these systems. They are designed mainly for large parallel calculations, without significant delays. The final processing of optical results is most often done in a computer, often using artificial intelligence methods (artificial neural network - ANN). Classic automatic recognition algorithms consist of two steps: vector's extraction of the characteristic features of objects from images, in which there is most often a high level of noise, and classification or identification. Hybrid (optoelectronic) systems play an important role among such systems
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