Abstract

A basis is provided for an image-analysis algorithm for automatic recognition, considered in this article from the viewpoint of formalizing the process of distinguishing clusters either of constant or similar signal intensity, their number and size, and two-level decision-making. Such an approach is based on the fractal hypothesis, which consists of assuming that the number of constant-intensity pixels in a cluster has a power dependence on its rank and that the pixels in the cluster itself have a fractal spatial distribution. The rationale of the hypothesis is associated with harmony of the variability and stability of the image as a system. The features of a two-level algorithm for automatic recognition by comparison with a standard are considered. An example of image recognition is presented, using an observed optical pattern. The features of such an approach when video information is analyzed on the basis of Kohonen patterns are studied.

© 2010 Optical Society of America

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