In a conventional pattern recognition system with a matched spatial filter (MSF), the system is based on a template matching which is the comparison of the test pattern with a number of stored patterns until an exact match is found. Therefore, sometimes, the system has not been able to distinguish some similar patterns. In this paper, we propose to apply a concept of feature extraction to matched spatial filtering to improve performance of the MSF for distinction of some closely similar patterns. The synthesis of the MSF with partial patterns of unknown input objects to be recognized enables filtering operation to extract desired features from some input patterns. Using this technique and a hybrid pattern recognition system with the MSF synthesized by nine feature extracted patterns, we could perfectly recognize a page of unknown 25 alphabets. The recognition result was given not by conventional peaks but by character symbols on a CRT display.
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