Historical Chinese Character Recognition Method Based on Style Transfer Mapping

Abstract

Historical Chinese character recognition has been a challenging topic in pattern recognition field because of large character set, various writing styles and lack of training samples. In this paper, we adopted Style Transfer Mapping (STM) method to historical Chinese character recognition. Optimal selection of parameters was discussed. Two sets of experiments were conducted. The first set of experiment was designed to test the performance of STM on different font styles by using available printed traditional Chinese characters. The second set of experiment was carried out on samples extracted from practical historical Chinese documents. Experimental results showed that supervised STM may improve the generalization ability of the classifier.