Binarization of Degraded Documents using Local Thresholding based on Moving Averages

Objectives: Image Binarization is the method which converts coloured and grayscale images into black and white images, black as foreground and white as background. This paper presents the new technique for binarization of degraded documents using moving averages. Methods/Statistical Analysis: Binarization of highly degraded images is very challenging task. In the proposed technique, moving averages is calculated horizontally and vertically by setting up the value of parameters. After this, local threshold value is calculated for every pixel based on moving averages within the local rectangular block both horizontally and vertically. Findings: The proposed method has been tested with large number of degraded documents and compared with existing techniques. The proposed technique makes use of the intensity of neighbouring pixels both upward and from left to right. The proposed method produce binarization results better when compared with existing Sauvola and Niblack’s Method. Applications: The proposed method produces a bianrized image which can be used in various applications like Optical character recognition, document layout analysis.