Abstract
For the disadvantage of traditional direction index histogram (DIH) handwriting identification method, an improved text-independent handwriting identification algorithm is presented. The handwriting image which is prepared to test needs pre-processing, then the normalized image can be obtained. Based on the features distance two factors can be extracted: the writing influence factor and the character influence factor. Compared the features of the handwriting image which is prepared to test with the features of the sample handwriting image, The better handwriting identification accuracy rate can be obtained, which provides problem-solving method for text-independent handwriting identification.
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