PURPOSE: To improve the recognition rate, by extracting phase geometrical features considering the deformation of the character after rough classification to a character group to which the input character belongs probably and collating these features with a phase geometrical feature dictionary to consider the occurrence frequency.
CONSTITUTION: Features of an input character 1 ("ji" in the example of figure) are extracted and are compared with contents of a dictionary to discriminate and extract a candidate category 2 ("ji", "ji", and "ji"). Simultaneously, the input character is inputted to a phase geometrical feature extracting part, and the outline is traced to count numbers of links and loops, and end points and crosses are detected and are counted. These phase geometrical features are compared with contents of a phase geometrical feature dictionary 3 considering the deformation of the character. In the example of figure, though characters A and B have the same phase geometrical features, the character A, namely, "ji" is selected as an answer on a basis of the occurrence frequency. Thus, the recognition rate of Kanji is improved easily.
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