Presents a fuzzy method for classification and recognition of separated handwritten characters. Linguistic expressions describing the individual characters are derived from a fuzzy model of a set of character samples. A small scale application of the method in which 26 lower-case cursive characters written by 30 different writers were analysed yielded 64% recognition rate. The method was also used to implement a character recogniser in a system for off-line recognition of cursive handwriting. In such a context, thanks to the use of a dictionary and a grammar parser, the recognition rate (at character level) rose to 96%.
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