Authors:
Lyu Bing
1
;
Hiroyuki Tomiyama
2
and
Lin Meng
2
Affiliations:
1
Graduate School of Science and Engineering, Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu, Shiga 525-8577, Japan
;
2
College of Science and Engineering, Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu, Shiga 525-8577, Japan
Keyword(s):
Text Line Segmentation, Early Japanese Books Understanding, Deep Learning, Image Processing.
Abstract:
Early Japanese books record a lot of information, and deciphering these pieces of ancient literature is very useful for researching history, politics, and culture. However, there are many early Japanese books that have not been deciphered. In recent years, with the rapid development of artificial intelligence technology, researchers are aiming to recognize characters in the early Japanese books through deep learning in order to decipher the information recorded in the books. However, these ancient literature are written in Kuzushi characters which is difficult to be recognized automatically for the reason for a large number of variation and joined-up style. Furthermore, the frame of article and the text line tilt increase the difficult recognition. This paper introduces a deep learning method for recognizing the characters, and proposal frame deletion and text line segmentation for helping Early Japanese Books understanding.