Moment-Based Pattern Representation Using Shape and Grayscale Features

A moment-based approach is developed to constructing tree-structured descriptions of patterns given by region-based shapes with grayscale attributes. The proposed representation is approximately invariant with respect to the pattern rotation, translation, scale, and level of brightness. The tree-like structure of the pattern representations provides their independent encoding into prefix code words. Due to this fact, a pattern recognition procedure amounts to decoding a code word of the pattern by the nearest code word from a tree of the code words of selected templates. Efficient application of the pattern representation technique is illustrated by experimental results on signature and hand gesture recognition.

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