Abstract
The paper is devoted to the use of spectral methods in problems of visual pattern recognition. The main idea is to associate a two-dimensional closed line, treated as a univariate function, with the contour of each object. On the basis of analysis of expansion coefficients of these functions, we propose adequate quantitative estimates for similarity of objects, which are invariant under affine transformations of the plane. A particular result is the invariance of the spectral representation with respect to the choice of the start-point. This invariance is obtained on the basis of the sine-cosine decomposition of arbitrary periodic functions.
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