Multi-stroke relaxation matching method for handwritten chinese character recognition

Abstract

Since Chinese characters can be represented by a set of basic line segments called sub-strokes, sub-strokes are often used as features to recognize handwritten Chinese Characters. However, the number of sub-strokes needed to evaluate a character are different due to handwriting variations and variations in the stroke extraction process. These differences in representation of the same character lower character recognition rate. A preliminary method to solve this problem is to merge several sub-strokes into a complete stroke. However, it is difficult to merge several sub-strokes into a correct and complete stroke because the Chinese character is not known in advance. In this paper, we propose a multi-stroke relaxation matching method to solve this problem. The proposed matching method can be divided into two parts; one is the multi-stroke relaxation process and the other is the multi-stroke select-match-pair process. The multi-stroke relaxation process will determine the optimal matching relations from the probability of each possible matching pair of sub-strokes and allow more than one of the sub-strokes to match with one or more additional sub-strokes by combining the merging steps into the relaxation process. The multi-stroke select-match-pair process is used to determine the stroke matching relation between the input and reference characters. Some experiments will be conducted to show the feasibility and correctness of the proposed algorithm. From the experimental results, we will prove that the proposed algorithm can solve the matching problem of different numbers of sub-strokes caused by handwriting variations and the stroke extraction process. For 2000 daily used Chinese characters, the actual recognition rate is 93.8 % and the cumulative recognition rate of the first five candidates is 98.9%.