Review on Image Enhancement Methods of Old Manuscript with Damaged Background

Abstract

Quite often old documents are subject to background damage. Examples of background damages are varying contrast, smudges, dirty background, ink through page, outdated paper and uneven background. The old Malay manuscripts which are a few hundred years of age, for example, are not legible even after preservation process by the library. Image processing offers a selection of approaches to counter these quality degradations and make the manuscripts readable. This paper provides a comprehensive review of the methods for enhancing old document images with damaged background. Three types of enhancement methods have been identified which are (a) image enhancement using binarization/ thresholding method, (b) image enhancement using a hybrid of binarization/thresholding and other methods, and (c) image enhancement using non-threshold based methods. Finally we found that the second method is becoming more popular and has a great potential for improvement in future.

Recovering Old Document Image by Using Hybrid Binrazation Technique.

“…The damage may come from lots of things such as environment like humidity and sunlight or damage also may be ink drop and uneven illumination on physical material. [1]These factors may effect on scientific and important cultural material. So to maintain these physical and ancient culture materials some of algorithms and ways are used to improve the quality and remove the clutter by using lots of filters on those materials [2].…”

An effective local contrast enhancement technique by blending of local statistics and Genetic Algorithm

“…Trans form domain method processes the image by trans forming the image to a specified domain and then transforms it back to the spatial domain. There are three recognized types of enhancement techniques they are (a) image enhancement utilizing binariza tion/thresholding method, (b) image enhancement utilizing hybrid of binarization/thresholding and other methods, and (c) image enhancement utilizing non threshold based methods [5].…”