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Fast Adaptive Image Binarization Using the Region Based Approach

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Artificial Intelligence and Algorithms in Intelligent Systems (CSOC2018 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 764))

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Abstract

Adaptive binarization of unevenly lightened images is one of the key issues in document image analysis and further text recognition. As the global thresholding leads to improper results making correct text recognition practically impossible, an efficient implementation of adaptive thresholding is necessary. The most popular global approach is the use of Otsu’s binarization which can be improved using the fast block based method or calculated locally leading to AdOtsu method. Even faster adaptive thresholding based on local mean calculated for blocks is presented in the paper. Obtained results have been compared with some other adaptive thresholding algorithms, being typically the modifications of Niblack’s method, for a set of images originating from DIBCO databases modified by addition of intensity gradients. Obtained results confirm the usefulness of the proposed fast approach for binarization of document images.

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Authors and Affiliations

  1. Department of Signal Processing and Multimedia Engineering, Faculty of Elecrtical Engineering, West Pomeranian University of Technology, Szczecin, 26 Kwietnia 10, 71-126, Szczecin, Poland

    Hubert Michalak & Krzysztof Okarma

Authors
  1. Hubert Michalak
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  2. Krzysztof Okarma
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Correspondence to Hubert Michalak .

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Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

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Michalak, H., Okarma, K. (2019). Fast Adaptive Image Binarization Using the Region Based Approach. In: Silhavy, R. (eds) Artificial Intelligence and Algorithms in Intelligent Systems. CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 764. Springer, Cham. https://doi.org/10.1007/978-3-319-91189-2_9

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