Separating text and background in degraded document images - a comparison of global thresholding techniques for multi-stage thresholding

Abstract

Before any processing of the textual content of a document image can be performed the text must be separated from the background of the image. Several thresholding algorithms have previously been proposed and are widely used in document processing. None have been shown effective at thresholding difficult documents where the background and foreground are non-uniform. In this paper we investigate the use of three global thresholding algorithms (Otsu's, Kapur's entropy and Solihin's quadratic integral ratio (QIR)) as the first stage in a multi-stage thresholding algorithm for use in degraded document images. It is concluded that Otsu's and Kapur's algorithms do not work well for difficult documents as they tend to over-threshold the image, thus losing much of the useful information. The QIR algorithm is more accurate in separating the foreground and background in these images, leaving a range of undecided, fuzzy, pixels for later processing in a subsequent stage.

A unified framework for document restoration using inpainting and shape-from-shading

“…One direction is based on binarization techniques such as the multi-stage binarization method proposed by Bar-Yosef et al to restore and recognize ancient Hebrew calligraphy documents [15]. Leedham et al [16] have investigated three global thresholding algorithms and a multi-stage thresholding algorithm to separate text from background in degraded document images and concluded that the given global algorithms do not work well with difficult documents due to over-thresholding while the multi-stage algorithm can do a better job by incrementally remove the noise. Another direction is to separate different layers using classification techniques especially in addressing the bleedthrough problem.…”

Word spotting for historical documents

“…This function is currently realized using a thresholding technique which we have found to be sufficient for our purposes. For more sophisticated foreground/background separation, see [11]. Using is ink, the upper and lower word profiles can be calculated as follows:…”

RSLDI: Restoration of single-sided low-quality document images

“…The problem of restoring a document image suffering from bleedthrough degradation, which is a major task in the analysis of very old documents, has been studied from several points of view [1][2][3][4][5][6][7][8][9]. The methods can be categorized in two groups: methods which work on double-sided document images, and methods which work on singlesided document images.…”