Abstract
We consider the recognition problem of Japanese historical handwritten characters called “Kuzushiji”. Unlike modern characters, Kuzushiji characters are harder to recognize partly because many of them are connected and not separated by spaces without any segmentation information. We propose two methods for segmentation and recognition of Kuzushiji characters. The first method learns segmentation rules and character classifiers simultaneously from data sets with character labels and segmentation information. Second method is for segmentation and can be used with any single character recognizer. Our methods outperform other baselines and achieve the state-of-the-art accuracy on both segmentation and recognition tasks on data sets of three consecutive Kuzushiji characters.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2019 Workshop on Historical Document Imaging and Processing, HIP 2019 |
| Publisher | Association for Computing Machinery |
| Pages | 72-77 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781450376686 |
| DOIs | |
| Publication status | Published - Sep 20 2019 |
| Event | 5th International Workshop on Historical Document Imaging and Processing, HIP 2019, held in conjunction with ICDAR 2019 - Sydney, Australia Duration: Sep 20 2019 → Sep 21 2019 |
Publication series
| Name | ACM International Conference Proceeding Series |
|---|
Conference
| Conference | 5th International Workshop on Historical Document Imaging and Processing, HIP 2019, held in conjunction with ICDAR 2019 |
|---|---|
| Country | Australia |
| City | Sydney |
| Period | 9/20/19 → 9/21/19 |
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All Science Journal Classification (ASJC) codes
- Human-Computer Interaction
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Software
Cite this
Recognition of Japanese historical hand-written characters based on object detection methods. / Tang, Yiping; Hatano, Kohei; Takimoto, Eiji.
Proceedings of the 2019 Workshop on Historical Document Imaging and Processing, HIP 2019. Association for Computing Machinery, 2019. p. 72-77 (ACM International Conference Proceeding Series).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Recognition of Japanese historical hand-written characters based on object detection methods
AU - Tang, Yiping
AU - Hatano, Kohei
AU - Takimoto, Eiji
PY - 2019/9/20
Y1 - 2019/9/20
N2 - We consider the recognition problem of Japanese historical handwritten characters called “Kuzushiji”. Unlike modern characters, Kuzushiji characters are harder to recognize partly because many of them are connected and not separated by spaces without any segmentation information. We propose two methods for segmentation and recognition of Kuzushiji characters. The first method learns segmentation rules and character classifiers simultaneously from data sets with character labels and segmentation information. Second method is for segmentation and can be used with any single character recognizer. Our methods outperform other baselines and achieve the state-of-the-art accuracy on both segmentation and recognition tasks on data sets of three consecutive Kuzushiji characters.
AB - We consider the recognition problem of Japanese historical handwritten characters called “Kuzushiji”. Unlike modern characters, Kuzushiji characters are harder to recognize partly because many of them are connected and not separated by spaces without any segmentation information. We propose two methods for segmentation and recognition of Kuzushiji characters. The first method learns segmentation rules and character classifiers simultaneously from data sets with character labels and segmentation information. Second method is for segmentation and can be used with any single character recognizer. Our methods outperform other baselines and achieve the state-of-the-art accuracy on both segmentation and recognition tasks on data sets of three consecutive Kuzushiji characters.
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UR - http://www.scopus.com/inward/citedby.url?scp=85074780655&partnerID=8YFLogxK
U2 - 10.1145/3352631.3352642
DO - 10.1145/3352631.3352642
M3 - Conference contribution
AN - SCOPUS:85074780655
T3 - ACM International Conference Proceeding Series
SP - 72
EP - 77
BT - Proceedings of the 2019 Workshop on Historical Document Imaging and Processing, HIP 2019
PB - Association for Computing Machinery
ER -