Image Enhancement Using Recursive Adaptive Gamma Correction

Abstract

The “Adaptive Approach for Historical or Degraded Document Binarization” is that in which Libraries and Museums obtain in large gathering of ancient historical documents printed or handwritten in native languages. Typically, only a small group of people are allowed access to such collection, as the preservation of the material is of great concern. In recent years, libraries have begun to digitize historical document that are of interest to a wide range of people, with the goal of preserving the content and making the documents available via electronic media. But for historical documents suffering from degradation due to damaged background, stained paper, holes and other factors, the recognition results drop appreciably. These recognition results can be improved using binarization technique. Binarization technique can differentiate text from background. The simplest way to get an image binarized is to choose a threshold value, and organize all pixels with values greater than this threshold as white, and every other pixels as black. The problem arises, how to select the correct threshold. The selection of threshold is performed by two methods: Global, Local. Our main focus is to effectively binarize the document images suffering from strain & smear, uneven backround, holes & spot and various illumination effect by applying Adaptive Binarization Techniques. Our objectives is to Study various Traditional Binarization Techniques and to develop a hybrid binarization technique which will be more efficient than traditional techniques in term of noise suppression, text extraction and enhance the document to make it better for readability & automatic Document analysis. Result is analyzed and obtains which conclude that.

Authors and Affiliations

Gurjeevan Kaur, Er. Jashanpreet Kaur

Keywords

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  • EP ID EP22963
  • DOI -
  • Views 249
  • Downloads 5

How To Cite

Gurjeevan Kaur, Er. Jashanpreet Kaur (2016). Image Enhancement Using Recursive Adaptive Gamma Correction. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 4(12), -. https://europub.co.uk/articles/-A-22963