It is very difficult to recognize cursive characters (kuzushiji) in classic Japanese literature. One of the difficulties is that multiple characters are connected. In this study, we propose a method for correctly recognizing consecutive kuzushiji characters by using multiple candidate regions as input to a neural network. An evaluation using an image database of three consecutive kuzushiji characters demonstrated that the proposed method had a higher accuracy rate than a method in which character detection preceded character recognition.
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