AUTOMATIC TEXT EXTRACTION FROM COMPLEX COLORED IMAGES USING GAMMA CORRECTION METHOD
- 1 , India
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.
DOI: https://doi.org/10.3844/jcssp.2014.705.715
Copyright: © 2014 G. Gayathri Devi and C. P. Sumathi. This is an open access article distributed under the terms of the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Gamma Correction
- GLCM
- Texture Measures
- Thresholding
- Text Region Extraction