Recognition of handprinted chinese characters via stroke relaxation

Abstract

A new relaxation matching method based on the information of the neighborhood relationship among extracted sub-strokes is proposed to recognize handprinted Chinese characters (HCCs). In order to ensure the convergence in the relaxation process, a new iterated scheme is devised. A supporting function is also designed to solve the problem of wide variability among writers and some inevitable defects in the preprocessing procedure. The distance function on which the matching possibilities of sub-strokes are reflected is determined by using the linear programming method to obtain the best result. The experiments are conducted by using the Kanji of the ETL-8 database. From the experimental results, it is shown that the proposed algorithm does improve the recognition rate of HCCs.