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Pattern recognition by primitive and subtracted patterns as a reference object for a matched spatial filter

In this paper, a new approach for uniquely selecting the optimum reference patterns of a matched spatial filter (MSF) is described. By the reference patterns we can synthesize the optimum MSF despite the target patterns are changed from letters to numerals, for example. In the experiment, two types of the reference patterns are used. One of the types is called primitive patterns which contain a vertical bar, horizontal bar and circle patterns. They are all orthogonal to each other in the view of image processing which means that three patterns are not similar shape at all. The other type patterns are given by subtraction of a few target patterns which the primitive reference patterns can not recognize. Using these reference patterns, an MSF was synthesized which could fairly recognize the 26 English alphabet letters.