A hybrid approach of automatic fuzzy rule generation for handwriting recognition
نویسندگان
چکیده
This paper presents a hybrid approach of automatic fuzzy rule generation for on-line handwriting recognition. The fuzzy rules contain the feature information extracted from a given prototype data set. The fuzzy statistical measures and neural networks are used to select the associative features from the input symbols. The final decision is enhanced through additional combination with expert’s knowledge. The rule base is coded in a dedicated fuzzy language for an interactive processing. The proposed method is applied to generate a rule base employing UNIPEN database for online recognition of isolated handwritten characters.
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