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The number of black points in each of the 25 nonoverlapping square regions of a size-normalized character matrix were used to recognize the 3822 uppercase handprinted alphabetic characters from Munson's multiauthor data set. The recognition accuracy obtained using a Bayes' classifier, which assumes statistically independent features, compares favorably with earlier results obtained using recognition systems having complexity comparable to ours. Included are results and a recommendation regarding system evaluation procedures.
Hussain et al. (Tue,) studied this question.
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