Restoration of Ancient Document Images Using Phase Based Binarization

Authors

  • V. Supaja  Assistant Professor, Department of ECE, Ravindra College of Engineering for Women, Kurnool, Andhra Pradesh, India
  • Saudagar Nikhath Afreen  Department of ECE, Ravindra College of Engineering for Women, Kurnool, Andhra Pradesh, India
  • P Thanmai  Department of ECE, Ravindra College of Engineering for Women, Kurnool, Andhra Pradesh, India
  • P Chaitanya Lahari  Department of ECE, Ravindra College of Engineering for Women, Kurnool, Andhra Pradesh, India
  • S. Sri Varsha  Department of ECE, Ravindra College of Engineering for Women, Kurnool, Andhra Pradesh, India

DOI:

https://doi.org//10.32628/IJSRSET229266

Keywords:

Historical document binarization, phase-derived features, document enhancement

Abstract

The main defects present in historical documents are darkness, non-uniform clarification, bleed-through and faded characters. To remove these defects binarization method is used. In this paper a phase based binarization method is studied in which phase of ancient document images is preserved. This method is derived in to three steps: preprocessing, main binarization and post processing. In preprocessing phase preserved denoised image is derived. In main binarization two phase feature maps are derived are maximum moment of phase congruency covariance and a locally weighted mean phase angle. At last in post processing Gaussian and median filter is use for enhancement of image. It is also improve the performance of binarization methodologies.

References

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Published

2022-04-30

Issue

Section

Research Articles

How to Cite

[1]
V. Supaja, Saudagar Nikhath Afreen, P Thanmai, P Chaitanya Lahari, S. Sri Varsha, " Restoration of Ancient Document Images Using Phase Based Binarization, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 9, Issue 2, pp.388-396, March-April-2022. Available at doi : https://doi.org/10.32628/IJSRSET229266