Model of identity verification support system based on voice and image samples

The increasing need to implement systems as identity verification meant that safe and effective verification systems have become one of the main branches of modern scientific research. In this paper, the idea of identity verification support system is presented. The main novelty of this work is to present the technique of feature extraction that can be implemented simultaneously for processed image files as well sound ones. Proposed method was tested due to achieve the highest possible accuracy of the selected neural classifier. The obtained results were discussed in terms of advantages and disadvantages for practical applications.