A unified framework based on the level set approach for segmentation of unconstrained double-sided document images suffering from bleed-through

Reza Farrahi Moghaddam, David Rivest-Hénault, Itay Bar-Yosef, Mohamed Cheriet

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

9 Scopus citations

Abstract

A novel method for the segmentation of double-sided ancient document images suffering from bleed-through effect is presented. It takes advantage of the level set framework to provide a completely integrated process for the segmentation of the text along with the removal of the bleed-through interfering patterns. This process is driven by three forces: 1) a binarization force based on an adaptive global threshold is used to identify region of low intensity, 2) a reverse diffusion force allows for the separation of interfering patterns from the true text, and 3) a small regularization force favors smooth boundaries. This integrated method achieves high quality results at reasonable computational cost, and can easily host other concepts to enhance its performance. The method is successfully applied to real and synthesized degraded document images. Also, the registration problem of the double-sided document images is addressed by introducing a level set method; the results are promising.

Original languageEnglish
Title of host publicationICDAR2009 - 10th International Conference on Document Analysis and Recognition
Pages441-445
Number of pages5
DOIs
StatePublished - 10 Dec 2009
EventICDAR2009 - 10th International Conference on Document Analysis and Recognition - Barcelona, Spain
Duration: 26 Jul 200929 Jul 2009

Publication series

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

Conference

ConferenceICDAR2009 - 10th International Conference on Document Analysis and Recognition
Country/TerritorySpain
CityBarcelona
Period26/07/0929/07/09

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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