This paper presents the results of experiments on the automatic recognition of few-pixel images in comparison with the data of visual recognition. The automatic recognition of few-pixel images is accomplished by means of an adaptive algorithm based on a compact description of the objects of an alphabet in the form of functional dependences of the mean values of the shape attributes and their rms deviations on the size of the image of an object and by using a fuzzy deciding rule with computation of confidence measures to hypotheses concerning the relation of the object to be recognized, applied to one of the objects of the alphabet. It is shown that applying an interpolation procedure to few-pixel images significantly increases the operating efficiency of the adaptive algorithm.

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