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Document binarization with automatic parameter tuning

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An Erratum to this article was published on 03 February 2013

Abstract

Document analysis systems often begin with binarization as a first processing stage. Although numerous techniques for binarization have been proposed, the results produced can vary in quality and often prove sensitive to the settings of one or more control parameters. This paper examines a promising approach to binarization based upon simple principles, and shows that its success depends most significantly upon the values of two key parameters. It further describes an automatic technique for setting these parameters in a manner that tunes them to the individual image, yielding a final binarization algorithm that can cut total error by one-third with respect to the baseline version. The results of this method advance the state of the art on recent benchmarks.

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Notes

  1. Some ambiguity remains over how to define the ground truth binarization. For instance, should an unintended ink spill made by a scribe be included? For the record, stipulate that the ground truth should identify the set of all pixels at least 50 % covered with ink during the production of the document. In practice, the ground truth used on most benchmark datasets probably does not correspond perfectly with this ideal, but represents the imperfect judgment of a human expert [4].

  2. The numbers for Lelore & Bouchara exclude image PR6 because its results were not available.

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Acknowledgments

The author thanks those who kindly shared results or implementation details of their algorithms for comparison purposes, including Basilis Gatos, Su Bolan, and Frédéric Bouchara.

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  1. Smith College, Northampton, MA, USA

    Nicholas R. Howe

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  1. Nicholas R. Howe
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Correspondence to Nicholas R. Howe.

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Howe, N.R. Document binarization with automatic parameter tuning. IJDAR 16, 247–258 (2013). https://doi.org/10.1007/s10032-012-0192-x

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  • DOI: https://doi.org/10.1007/s10032-012-0192-x

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