Text Localization and Extraction from Complex Gray Images

  • Farshad Nourbakhsh
  • Peeta Basa Pati
  • A. G. Ramakrishnan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4338)


We propose two texture-based approaches, one involving Gabor filters and the other employing log-polar wavelets, for separating text from non-text elements in a document image. Both the proposed algorithms compute local energy at some information-rich points, which are marked by Harris’ corner detector. The advantage of this approach is that the algorithm calculates the local energy at selected points and not throughout the image, thus saving a lot of computational time. The algorithm has been tested on a large set of scanned text pages and the results have been seen to be better than the results from the existing algorithms. Among the proposed schemes, the Gabor filter based scheme marginally outperforms the wavelet based scheme.


Corner Point Delaunay Triangulation Document Image Gabor Filter Text Region 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Farshad Nourbakhsh
    • 1
  • Peeta Basa Pati
    • 1
  • A. G. Ramakrishnan
    • 1
  1. 1.MILE Laboratory, Department of EEIndian Institute of ScienceBangaloreIndia

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