Improved Degraded Document Image Binarization Using Median Filter for Background Estimation

Mehdi Khitas, Lahcene Ziet, Saad Bouguezel


In this paper, we propose a new binarization method suitable for images having a variety of sizes and degradation levels. It is mainly based on the idea of estimating a document background surface by new smoothing approach through a median filter and compute-Sharp-Peak to replace iterative polynomial. The resulting document image is then segmented by a global threshold binarization. The simulation results confirm that the performance of the proposed method is generally competitive to that of the existing methods. For highly degraded document images, specifically the documents in the BICKLEY DIARY data-base, the performance of the former is substantially better than that of the latter. We show how this approach outperforms the existing and widely used binarization methods in terms of accuracy, F-measure, PSNR, NRM, MPM, DRD, recall and precision.



Thresholding; binarization; Document image analysis; Histogram analysis; Old documents analysis; Handwritten and printed documents; Background estimation; Median filter.

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Print ISSN: 1392-1215
Online ISSN: 2029-5731