Character recognition in Japanese historical documents via adaptive multi-region model

Yueyu Wang, Seiichiro Kamata

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

Abstract

In this work, we introduce a novel model with an adaptive multi-region extraction network to grasp multi-aspect of discriminative features, because feature inside bounding box is insufficient for classification, and normal models are sensitive to inaccuracy of predicted bounding boxes. We use the new model to recognize Japanese from historical documents. This model can be trained end-to-end without any extra supervision. The resulting CNN-based representation has abundant of features, containing the contextual information together with center part information. These features are helpful and crucial for classification. Based on this model, we also propose a data augmentation method using both local and global data distortion to generate diversified samples in order to solve the problem of data imbalance. Experiments show that with the usage of our model, we get a better result in ancient Japanese dataset.

Original languageEnglish
Title of host publication2018 Joint 7th International Conference on Informatics, Electronics and Vision and 2nd International Conference on Imaging, Vision and Pattern Recognition, ICIEV-IVPR 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages404-409
Number of pages6
ISBN (Electronic)9781538651612
DOIs
Publication statusPublished - 2019 Feb 12
EventJoint 7th International Conference on Informatics, Electronics and Vision and 2nd International Conference on Imaging, Vision and Pattern Recognition, ICIEV-IVPR 2018 - Kitakyushu, Japan
Duration: 2018 Jun 252018 Jun 28

Publication series

Name2018 Joint 7th International Conference on Informatics, Electronics and Vision and 2nd International Conference on Imaging, Vision and Pattern Recognition, ICIEV-IVPR 2018

Conference

ConferenceJoint 7th International Conference on Informatics, Electronics and Vision and 2nd International Conference on Imaging, Vision and Pattern Recognition, ICIEV-IVPR 2018
CountryJapan
CityKitakyushu
Period18/6/2518/6/28

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ASJC Scopus subject areas

  • Signal Processing
  • Control and Optimization
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems

Cite this

Wang, Y., & Kamata, S. (2019). Character recognition in Japanese historical documents via adaptive multi-region model. In 2018 Joint 7th International Conference on Informatics, Electronics and Vision and 2nd International Conference on Imaging, Vision and Pattern Recognition, ICIEV-IVPR 2018 (pp. 404-409). [8641033] (2018 Joint 7th International Conference on Informatics, Electronics and Vision and 2nd International Conference on Imaging, Vision and Pattern Recognition, ICIEV-IVPR 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIEV.2018.8641033