The National Diet Library’s digital collection contains about 400, 000 valuable books from the Meiji period to the early Showa period. The books are stored as image data and have not been converted into text. Therefore, the use of information is limited. There are manual and automatic methods of texting Early–modern Japanese printed book, but manual methods cost a fortune. OCR is used for automation, but Early–modern Japanese printed book’s characteristics reduce recognition rates. Therefore, it is necessary to develop a character recognition method specific to Early–modern Japanese printed book. Collecting Early–modern Japanese printed character is also manual, and it is difficult to collect many characters evenly. In this paper, we propose a method to improve Early–modern Japanese printed character recognition accuracy using images generated from modern characters. CycleGAN is used to generate images of modern characters from modern characters. The generated image is incorporated into train data to create a character recognition model. The experiment showed that the recognition rate was improved by using the generated image in train data.