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DSD: document sparse-based denoising algorithm

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Abstract

In this paper, we present a sparse-based denoising algorithm for scanned documents. This method can be applied to any kind of scanned documents with satisfactory results. Unlike other approaches, the proposed approach encodes noise documents through sparse representation and visual dictionary learning techniques without any prior noise model. Moreover, we propose a precision parameter estimator. Experiments on several datasets demonstrate the robustness of the proposed approach compared to the state-of-the-art methods on document denoising.

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Acknowledgements

This work was partially supported by the European project SCANPLAN (A0806017L), the Spanish ConCORDIA Project (TIN2015-70924-C2-2-R) and the Vietnam National University, Hanoi (VNU) under project number QG.18.04.

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Authors and Affiliations

  1. Department Informatics, Faculty of Mathematics Mechanics Informatics, VNU University of Science, Hanoi, Vietnam

    T. H. Do

  2. Computer Vision Center, Computer Science Department, Engineering School, Universitat Autònoma de Barcelona, 08193, Bellaterra, Catalonia, Spain

    O. Ramos Terrades

  3. LORIA - UMR 7503, Université de Lorraine, Campus Scientifique, BP 239, 54506, Vandoeuvre-lès-Nancy, France

    S. Tabbone

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  1. T. H. Do
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  2. O. Ramos Terrades
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  3. S. Tabbone
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Correspondence to O. Ramos Terrades.

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Do, T.H., Ramos Terrades, O. & Tabbone, S. DSD: document sparse-based denoising algorithm. Pattern Anal Applic 22, 177–186 (2019). https://doi.org/10.1007/s10044-018-0714-3

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  • DOI: https://doi.org/10.1007/s10044-018-0714-3

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