Degraded Document Image Binarization Using Segmentation Algorithm

Degraded document image binarization is very difficult process due to different types of degradation over the document. Multiple algorithms as well as methods are available to get clear image of degraded document image. Many researchers have worked in this field of image processing. Still there is scope to get more clear and upgraded document image. Image segmentation is very famous process in the image processing domain. Image segmentation can used to binarize degraded document image. Binarization is a process to generate binary image from gray scale image. Also it is tedious to differentiate foreground and background pixel due to degradation. In this paper, Image Segmentation using thresholding is proposed for degraded document image binarization. Image segmentation gives better result than canny edge approach. DOI: 10.17762/ijritcc2321-8169.150611

Document image restoration - For document images scanned from bound volumes -

Ph.DDOCTOR OF PHILOSOPH

THRESHOLDING USING AN ILLUMINATION MODEL

Most grey level thresholding methods produce good results in situations where the illumination gradient in the original raster image is regular and not too large. In other cases, such as a large linear change in illumination, a satisfactory bi-level image cannot be produced. If the object pixels can be identified in a variety of positions throughout the image, these can be used to construct a surface whose height is related to illumination at each pixel. This estimate can be used to produce a threshold for each pixel. The method described here uses the Shen-Castan edge detector to identify object pixels, and creates a surface using a moving least squares method that can be used to threshold the image.We are currently acquiring citations for the work deposited into this collection. We recognize the distribution rights of this item may have been assigned to another entity, other than the author(s) of the work.If you can provide the citation for this work or you think you own the distribution rights to this work please contact the Institutional Repository Administrator at [email protected]