PURPOSE: To execute the character recognition at a high correct answer rate even with regard to a character group such as a handwritten KANA (Japanese syllabary) character by discriminating a final character recognition result from in each character pattern candidate discriminated by plural neural nets, respectively.

CONSTITUTION: In a grouping neural net 11, weighting related to grouping of an input character pattern is executed, and in each neural net 12 - 31, learning between character pattern candidates classified at every similar character, respectively and the discrimination of character recognition result are executed. Subsequently, a final discriminating part 32 compares output results of each neural nets 12 - 31, and outputs that of the largest value as a final character recognition result. In such a way, even with regard to a character group having many kinds of characters such as handwritten KANA characters, and many similar patterns, the character recognition can be executed at a high correct answer rate.