Using Neural Networks Application for the Font Recognition Task Solution

The purpose of the paper is research and development of font visual classification system, that will allow users to work with fonts more effectively, specifically with the use of the required font fetching on pre-screening, employment of the wide range of filters and font management tools application.There were reviewed basic fonts classification approaches with the definition of pivot advantages and disadvantages. After assessing these approaches, it was decided to deploy neural network with the font symbols images as an input.As a result, neural networks driven computer fonts classification system, that allows to classify fonts by slope, basic style and weight according to their graphical representation, was developed and integrated into the font organizer. High classification accuracy of the developed neural network model was confirmed by control tests. Percentage of correctly classified fonts during the system testing reaches 91% in determining weight, 92% in determining basic style, 96% in determining slope. The developed system can be applied to tasks of fonts classification solution as supplement for digital documents structure determination, and as system of font selection for design creation.