Research Article Open Access

AUTOMATIC TEXT EXTRACTION FROM COMPLEX COLORED IMAGES USING GAMMA CORRECTION METHOD

C. P. Sumathi1 and G. Gayathri Devi1
  • 1 , India
Journal of Computer Science
Volume 10 No. 4, 2014, 705-715

DOI: https://doi.org/10.3844/jcssp.2014.705.715

Submitted On: 18 August 2013 Published On: 24 December 2013

How to Cite: Sumathi, C. P. & Devi, G. G. (2014). AUTOMATIC TEXT EXTRACTION FROM COMPLEX COLORED IMAGES USING GAMMA CORRECTION METHOD. Journal of Computer Science, 10(4), 705-715. https://doi.org/10.3844/jcssp.2014.705.715

Abstract

The aim of this study is to propose a new methodology for text region extraction and non text region removal from complex background colored images. This study presents a new approach based on Gamma correction by determining a gamma value for enhancing the foreground details in an image. The approach also uses gray level co-occurrence matrices, texture measures, threshold concepts. The proposed method is a useful preprocessing technique to remove non text region and to show the text region in the image. Experiments were on various images from the datasets collected and tagged by the ICDAR robust reading dataset collection team. Experimental results show that the proposed method has a good performance on extracting text regions in an image.

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Keywords

  • Gamma Correction
  • GLCM
  • Texture Measures
  • Thresholding
  • Text Region Extraction