Recognition of Japanese historical hand-written characters based on object detection methods

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish
Title of host publicationProceedings of the 2019 Workshop on Historical Document Imaging and Processing, HIP 2019
PublisherAssociation for Computing Machinery
Pages72-77
Number of pages6
ISBN (Electronic)9781450376686
DOIs
Publication statusPublished - Sep 20 2019
Event5th International Workshop on Historical Document Imaging and Processing, HIP 2019, held in conjunction with ICDAR 2019 - Sydney, Australia
Duration: Sep 20 2019Sep 21 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference5th International Workshop on Historical Document Imaging and Processing, HIP 2019, held in conjunction with ICDAR 2019
CountryAustralia
CitySydney
Period9/20/199/21/19

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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  • Cite this

    Tang, Y., Hatano, K., & Takimoto, E. (2019). Recognition of Japanese historical hand-written characters based on object detection methods. In Proceedings of the 2019 Workshop on Historical Document Imaging and Processing, HIP 2019 (pp. 72-77). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3352631.3352642