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An adaptive water flow model for binarization of degraded document images

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Abstract

In this paper, we present an adaptive water flow model for the binarization of degraded document images. We regard an image surface as a three-dimensional terrain and pour water on it. The water finds the valleys and fills them. Our algorithm controls the rainfall process, pouring the water, in such a way that the water fills up to half of the valley’s depth. After stopping the rainfall, each wet region represents one character or a noisy component. To segment each character, we labeled the wet regions and regarded them as blobs; since some of the blobs are noisy components, we use a multilayer Perceptron to label each blob as either text or non-text. Since our algorithm classifies the blobs instead of pixels, it preserves stroke connectivity. After several experiments, the proposed binarization algorithm demonstrated superior performance against six well-known algorithms on three sets of degraded document images. The main superiority of our algorithm is on document images with uneven illumination.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Tarbiat Modarres University, P.O. Box 14115-143, Tehran, Iran

    Morteza Valizadeh & Ehsanollah Kabir

Authors
  1. Morteza Valizadeh
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  2. Ehsanollah Kabir
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Correspondence to Morteza Valizadeh.

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Valizadeh, M., Kabir, E. An adaptive water flow model for binarization of degraded document images. IJDAR 16, 165–176 (2013). https://doi.org/10.1007/s10032-012-0182-z

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  • DOI: https://doi.org/10.1007/s10032-012-0182-z

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