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In this paper, a comparative analysis of the correlation-extreme method, the method of contour analysis and the method of stochastic gradient identification in the objects identification for a binary image is carried out. The results are obtained for a situation where possible deformations of an identified object with respect to a pattern can be reduced to a similarity model, that is, the pattern and the object may differ in scale, orientation angle, shift along the base axes, and additive noise. The identification of an object is understood as the recognition of its image with an estimate of the strain parameters relative to the template.

This article considers the detection of objects on the time sequences of satellite multizone images. Optimal and quasi-optimal detection algorithms are built on the basis of a combination of non-linear double stochastic filters and pseudo-gradient procedures. The analysis of behavior of the synthesized algorithms at processing of the real satellite material under conditions of a priori uncertainty concerning parameters of deformation of the reference image is carried out.

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