Weakly Supervised Learning for Over-Segmentation Based Handwritten Chinese Text Recognition

Zhen Xing Wang, Qiu Feng Wang, Fei Yin, Cheng Lin Liu

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

16 Citations (Scopus)

Abstract

In this paper, we proposed a weakly supervised learning method for string-level training of character classifier in over-segmentation based handwritten Chinese text recognition (HCTR). The over-segmentation based framework can easily integrate multiple context models and provide accurate character boundary and recognition confidence, but has not been implemented with string-level training for HCTR. We propose to optimize the character classifier by minimizing the marginal log-likelihood on a string-level annotated handwriting dataset, where the forward-backward algorithm is utilized in a segmentation-and-recognition lattice. Experimental results on the CASIA-HWDB and ICDAR-2013 competition datasets show that the proposed method improves the recognition performance significantly, which demonstrates its effectiveness.

Original languageEnglish
Title of host publicationProceedings - 2020 17th International Conference on Frontiers in Handwriting Recognition, ICFHR 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages157-162
Number of pages6
ISBN (Electronic)9781728199665
DOIs
Publication statusPublished - Sept 2020
Event17th International Conference on Frontiers in Handwriting Recognition, ICFHR 2020 - Dortmund, Germany
Duration: 7 Sept 202010 Sept 2020

Publication series

NameProceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR
Volume2020-September
ISSN (Print)2167-6445
ISSN (Electronic)2167-6453

Conference

Conference17th International Conference on Frontiers in Handwriting Recognition, ICFHR 2020
Country/TerritoryGermany
CityDortmund
Period7/09/2010/09/20

Keywords

  • character classifier
  • handwritten Chinese text recognition
  • oversegmentation
  • string-level training
  • weakly supervised learning

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