A model for the gray-intensity distribution of historical handwritten documents and its application for binarization

  • Marte A. Ramírez-Ortegón
  • Lilia L. Ramírez-RamírezEmail author
  • Ines Ben Messaoud
  • Volker Märgner
  • Erik Cuevas
  • Raúl Rojas
Original Paper


In this article, our goal is to describe mathematically and experimentally the gray-intensity distributions of the fore- and background of handwritten historical documents. We propose a local pixel model to explain the observed asymmetrical gray-intensity histograms of the fore- and background. Our pixel model states that, locally, the gray-intensity histogram is the mixture of gray-intensity distributions of three pixel classes. Following our model, we empirically describe the smoothness of the background for different types of images. We show that our model has potential application in binarization. Assuming that the parameters of the gray-intensity distributions are correctly estimated, we show that thresholding methods based on mixtures of lognormal distributions outperform thresholding methods based on mixtures of normal distributions. Our model is supported with experimental tests that are conducted with extracted images from DIBCO 2009 and H-DIBCO 2010 benchmarks. We also report results for all four DIBCO benchmarks.


Binarization Thresholding Normal Historical documents Handwritten  DIBCO 



We would like to thanks to the Asociación Mexicana de Cultura A.C. We are so grateful to the editor and all the reviewers for their constructive and meticulous comments.

Supplementary material

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Marte A. Ramírez-Ortegón
    • 1
  • Lilia L. Ramírez-Ramírez
    • 2
    Email author
  • Ines Ben Messaoud
    • 3
  • Volker Märgner
    • 4
  • Erik Cuevas
    • 5
  • Raúl Rojas
    • 6
  1. 1.División Académica de Ciencias BásicasUJATCunduacánMexico
  2. 2.Instituto Tecnológico Autónomo de México (ITAM)MexicoMexico
  3. 3.Laboratoire des Systèmes et Traitement de SignalLSTS Ecole Nationale dIngénieurs de Tunis, ENIT TunisTunisTunisia
  4. 4.Institüt für NachrichtentechnikTechnische Universität BraunschweigBraunschweigGermany
  5. 5.Departamento de Ciencias ComputacionalesUniversidad de GuadalajaraGuadalajaraMexico
  6. 6.Institüt für InformatikFreie Universität BerlinBerlinGermany

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