Dewarping of document image by global optimization

Hironori Ezaki, Seiichi Uchida, Akira Asano, Hiroaki Sakoe

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

31 Citations (Scopus)

Abstract

This paper proposes a novel dewarping technique for document images of bound volumes. This technique is a kind of model fitting techniques for estimating the warp of each text line by fitting some elastic curve model to the text line. Differing from conventional techniques, the proposed technique is applicable to document images including local irregularities such as formulae, short text lines, and figures, since the proposed technique dewarps whole document images by fitting splines while considering the global optimality that specifies the desirable relationship among the splines. The experimental results on several document images including the local irregularities indicated the effectiveness of the proposed technique. The experimental result also indicated the effectiveness of the vertical division of a document image into some partial document images for more accurate dewarping.

Original languageEnglish
Title of host publicationProceedings of the Eighth International Conference on Document Analysis and Recognition
Pages302-306
Number of pages5
DOIs
Publication statusPublished - Dec 1 2005
Event8th International Conference on Document Analysis and Recognition - Seoul, Korea, Republic of
Duration: Aug 31 2005Sep 1 2005

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Volume2005
ISSN (Print)1520-5363

Other

Other8th International Conference on Document Analysis and Recognition
CountryKorea, Republic of
CitySeoul
Period8/31/059/1/05

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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  • Cite this

    Ezaki, H., Uchida, S., Asano, A., & Sakoe, H. (2005). Dewarping of document image by global optimization. In Proceedings of the Eighth International Conference on Document Analysis and Recognition (pp. 302-306). [1575558] (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR; Vol. 2005). https://doi.org/10.1109/ICDAR.2005.87