  Recognition of historical documents is a challenging problem due to the
noised, damaged characters and background. However, in Japanese historical
documents, not only contains the mentioned problems, pre-modern Japanese
characters were written in cursive and are connected. Therefore, character
segmentation based methods do not work well. This leads to the idea of creating
a new recognition system. In this paper, we propose a human-inspired document
reading system to recognize multiple lines of premodern Japanese historical
documents. During the reading, people employ eyes movement to determine the
start of a text line. Then, they move the eyes from the current character/word
to the next character/word. They can also determine the end of a line or skip a
figure to move to the next line. The eyes movement integrates with visual
processing to operate the reading process in the brain. We employ
attention-based encoder-decoder to implement this recognition system. First,
the recognition system detects where to start a text line. Second, the system
scans and recognize character by character until the text line is completed.
Then, the system continues to detect the start of the next text line. This
process is repeated until reading the whole document. We tested our
human-inspired recognition system on the pre-modern Japanese historical
document provide by the PRMU Kuzushiji competition. The results of the
experiments demonstrate the superiority and effectiveness of our proposed
system by achieving Sequence Error Rate of 9.87% and 53.81% on level 2 and
level 3 of the dataset, respectively. These results outperform to any other
systems participated in the PRMU Kuzushiji competition.
