(untitled) (International Journal of Engineering and Computer Science, 2014)
Binarization is a process of separation of pixel values of an input image into two pixel values like white as background and black as foreground. It is an important part in image processing and the first step in many document analysis and OCR processes. Most of the binarization techniques associate a certain intensity value called threshold. Each and every pixel of the concerned grayscale input image should be compared with the threshold value and according to it, pixels are separated into two classes background and foreground. Thus threshold plays a major role in binarization and choosing of an appropriate threshold value is an important one. It can be approached by two ways, first is the global thresholding and second is the local thresholding techniques. The global thesholding are suitable for converting any grayscale image into a binary form but are inappropriate for complex documents, and degraded documents. If the illumination over the document is not uniform, it produces marginal noise along the page borders. To overcome these complexities, local thresholding techniques have been proposed for document binarization. These techniques estimate a different threshold for each pixel according to the grayscale information of the neighboring pixels. In this paper various local thresholding techniques are compared