Off-Line Chinese Handwriting Identification Based on Stroke Shape and Structure

Handwriting identification is a hot topic in the field of pattern recognition. In this paper, we propose a novel method for off-line Chinese handwriting identification based on stroke shape and structure. To extract the features embedded in Chinese handwriting character, two special structures have been explored, which are bounding rectangle and TBLR quadrilateral. 16 features are extracted from the two structures, which are used to compute the unadjusted similarity, and the other 4 commonly used features are also computed to adjust the similarity adaptively. The final identification is performed on the similarity. Experimental results on the SYSU database have validated the effectiveness of the proposed method.