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Gabor filter-based texture for ancient degraded document image binarization

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Abstract

Binarization of ancient degraded document images is a very important step for their preservation and digital use. In this paper, a new simple threshold-based method is proposed for binarization of ancient degraded documents. The proposed method is inspired from the most popular threshold-based methods by exploiting texture information features extracted from both the filtered image using the Gabor filter and the original degraded document. Firstly, a preprocessing stage using the Wiener filter is performed on the degraded image for facilitating the binarization. Then, a Gabor filter bank is weighted according to the dominant slant of the document’s image script for estimating the binarization threshold. Finally, a post-processing stage is applied based on morphological operator for reducing some artifacts. For setting optimal parameters, a new protocol is proposed in the design stage by taking into account the degradation type. Exhaustive experiments are achieved using standard DIBCO datasets series reorganized according to the degradation type and the year of contest. Obtained results are compared against various well-known threshold-based methods. On the other hand, a comparison is achieved with the state-of-the-art methods. Promising results and stability are noticed for the proposed technique, specifically for ink bleed-through degradation and low-contrasted documents.

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Acknowledgements

This work was supported by le Fond National de la Recherche Scientifique et du Développement Technologique, Ministère de l’Enseignement Supérieur et de la Recherche Scientifique, Algiers, Algeria.

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Authors and Affiliations

  1. Laboratoire d’Ingénierie des Systèmes Intelligents et Communicants, Faculty of Electronics and Computer Science, University of Science and Technology Houari Boumediene (USTHB), 32, El Alia, 16111, Bab Ezzouar, Algiers, Algeria

    Abdenour Sehad & Youcef Chibani

  2. McGill University, 805 Sherbrook St. West, Burnside Hall 314, Montreal, H3A-0B9, Canada

    Rachid Hedjam

  3. ETS, Ecole de Technologie Supérieure, Montréal, QC, H3C 1K3, Canada

    Mohamed Cheriet

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  1. Abdenour Sehad
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  2. Youcef Chibani
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  3. Rachid Hedjam
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  4. Mohamed Cheriet
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Correspondence to Abdenour Sehad.

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Sehad, A., Chibani, Y., Hedjam, R. et al. Gabor filter-based texture for ancient degraded document image binarization. Pattern Anal Applic 22, 1–22 (2019). https://doi.org/10.1007/s10044-018-0747-7

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