Advertisement

Text Enhancement by PDE’s Based Methods

  • Zouhir Mahani
  • Jalal Zahid
  • Sahar Saoud
  • Mohammed El Rhabi
  • Abdelilah Hakim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7340)

Abstract

In this work, we propose a new method to enhance text in document-image. Firstly, we introduce a classical model and a way to solve it by means of a non-convex optimization problem. So, a simoultaneaous estimation of the reflectance and the luminance is obtained when the non uniform illumination (also called luminance) is a smooth function and the reflectance is a function of bounded variation. We give an analyse of this problem and some conditions of existence and unicity. Then, we consider the “log” of the classical model. A new pde’s model is proposed. This method is based on the resolution of an original partial differential equation (PDE) estimating the log of the luminance. We assume that the luminance is enough smooth and is the solution of a non classical second order’s PDE.Then we deduce the reflectance from the estimated luminance and the acquired image. The effectiveness and the robustness of the proposed process are shown on numerical examples in real-world situation (images acquired from cameraphones). Then, we illustrate the ability of this method to improve an Optical Character Recognition (OCR) in text recognition.

Keywords

Document Image Optical Character Recognition Shutter Speed Camera Phone Uniform Illumination 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Wu, J., Caelli, T.: Model Based 3D object localization and recognization from a single intensity image. In: Adam, K., Tony, K., Cheng, S.Y. (eds.) Computer Vision and Shape Recognition, pp. 21–67 (1988)Google Scholar
  2. 2.
    Baird, H.S.: The State of the Art of Document Image Degradation Modeling. In: Proc. of 4th IAPR International Workshop on Document Analysis Systems, Rio de Janeiro, pp. 1–16 (2000)Google Scholar
  3. 3.
    Drira, F., Le Bourgeois, F., Emptoz, H.: Document images restoration by a new tensor based diffusion process: Application to the recognition of old printed documents. In: 10th International Conference on Document Analysis and Recognition (ICDAR 2009), Barcelone, pp. 321–325 (2009)Google Scholar
  4. 4.
    Moghaddam, R.F., Cheriet, M.: RSLDI: Restoration of single-sided low-quality document images. Pattern Recognition, Special Issue on Handwriting Recognition (42), 3355–3364 (2009)Google Scholar
  5. 5.
    Horn, B.K.: Robot Vision. MIT Press (1986)Google Scholar
  6. 6.
    Kim, J., Lee, H.: Joint nonuniform illumination estimation and deblurring for bar code signals. Optic Express 15(22), 14817–14837 (2007)CrossRefGoogle Scholar
  7. 7.
    Dumas, L., El Rhabi, M., Rochefort, G.: An evolutionary approach for blind deconvolution of barcode images with nonuniform illumination. In: IEEE Congress on Evolutionary Computation, pp. 2423–2428 (2011)Google Scholar
  8. 8.
    Martin, A., Lefèbure, M.: Realeyes3D SA, patent, http://www.prior-ip.com/application/33411968/
  9. 9.
    Gross, R., Brajovic, V.: An Image Preprocessing Algorithm for Illumination Invariant Face Recognition. In: Kittler, J., Nixon, M.S. (eds.) AVBPA 2003. LNCS, vol. 2688, pp. 10–18. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  10. 10.
    Barrow, H.G., Tenenbaum, J.M.: Recovering intrinsic scene characteristics from images. In: CVS 1978, p. 326 (1978)Google Scholar
  11. 11.
    Laszlo, S.-K.: Monte-Carlo Global Illumination Methods - State of the Art and New Developments. In: SCCG 1999 (1999) (invited talk)Google Scholar
  12. 12.
    Cohen, A., Wolfgang, D., Daubechies, I., DeVore, R.: Harmonic analysis of the space BV. Rev. Mat. Iberoamericana 19(1), 235–263 (2003)MathSciNetzbMATHCrossRefGoogle Scholar
  13. 13.
    Giusti, E.: Minimal Surfaces and Functions of Bounded Total Variation. Monographs in Mathematics, vol. 80. Birkhauser, Boston (1984)Google Scholar
  14. 14.
    El Rhabi, M., Rochefort, G.: Realeyes3D SA, patent, http://www.wipo.int/patentscope/search/en/WO2009112710

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Zouhir Mahani
    • 1
  • Jalal Zahid
    • 1
  • Sahar Saoud
    • 1
  • Mohammed El Rhabi
    • 2
  • Abdelilah Hakim
    • 2
  1. 1.ESTA, Laboratoire Matriaux, Systémes et Technologies de l’informationUniversité Ibn ZohrAgadirMorocco
  2. 2.Faculté des Sciences et Techniques - Guéliz (FSTG), Laboratoire de Mathématiques Appliquées et InformatiqueUniversité Cadi AyyadGuélizMorocco

Personalised recommendations