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With the growth of production automation, it became necessary to ensure the operation of many technological processes without human participation. These are mainly the processes associated with routine, repetitive work or dangerous to humans. Such processes include the classification of objects. Vision systems can be used to solve this problem. Today, visual control systems are widely in demand in various fields of science, industry and technology. In particular, they are used to obtain data on monitoring the state of objects, their location, and recognizing any objects of different forms. In this paper, it is proposed to test the applicability of the FOREL clustering algorithms for solving the problem of classifying individual flat objects based on their dimensionless features. The result of the work will be the probabilities of recognition of each object from a given test sample, on the basis of which it will be possible to draw a conclusion about the applicability of this method for solving the formulated problem.

CLASSIFICATION OF INDIVIDUAL FLAT OBJECTS BY THE FOREL METHOD