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Handwriting has continued to persist as a means of communication and recording information in day-to-day life even with the introduction of new technologies. Given its ubiquity in human transactions, machine recognition of handwriting has practical significance, as in reading handwritten notes in a Personal Digital Assistant (PDA), in postal addresses on envelopes, in amounts in back checks, in handwritten fields, in forms etc., to solve the problem of writer identification with intermediate classes (writers) and objects (characters), it is a good way to extract the features with clear physical meanings. The extracted features are in variant under translation scaling and stroke width.
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