Abstract
A large amount of similar Chinese characters is one of the main reasons to cause the high reject rate and substitution rate. In this paper, an innovative similar characters recognition method based on multi-resolution feature space is proposed. The process includes originally abstracting global feature vectors, progressively, dynamically and recursively adding finer local feature vectors to improve the ability of recognition and finally achieving the result which satisfies the conditions. In this way, it is not necessary to decide similar character sets manually since it can automatically choose the space in the largest difference of similar characters to construct new feature space. The efficiency of this method was proved by the experiments which effectively improved the recognition rate of similar characters
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