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Generic Document Image Dewarping by Probabilistic Discretization of Vanishing Points

Abstract : Document images dewarping is still a challenge especially when documents are captured with one camera in an uncontrolled environment. In this paper we propose a generic approach based on vanishing points (VP) to reconstruct the 3D shape of document pages. Unlike previous methods we do not need to segment the text included in the documents. Therefore, our approach is less sensitive to pre-processing and segmentation errors. The computation of the VPs is robust and relies on the a-contrario framework, which has only one parameter whose setting is based on probabilistic reasoning instead of experimental tuning. Thus, our method can be applied to any kind of document including text and non-text blocks and extended to other kind of images. Experimental results show that the proposed method is robust to a variety of distortions.
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Submitted on : Tuesday, November 3, 2020 - 2:46:48 PM
Last modification on : Wednesday, November 3, 2021 - 7:10:23 AM
Long-term archiving on: : Thursday, February 4, 2021 - 6:37:22 PM


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  • HAL Id : hal-02987029, version 1



Gilles Simon, Salvatore Tabbone. Generic Document Image Dewarping by Probabilistic Discretization of Vanishing Points. ICPR 2020 - 25th International Conference on Pattern Recognition, Sep 2020, Milan / Virtual, Italy. ⟨hal-02987029⟩



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