Documents often exhibit various forms of degradation, which make it hard to be read and
substantially deteriorate the performance of an OCR system. In this paper, we propose an …

The binarization of degraded document images is a challenging problem in terms of
document analysis. Binarization is a classification process in which intra-image pixels are …

This paper presents an effective approach for the local threshold binarization of degraded
document images. We utilize the structural symmetric pixels (SSPs) to calculate the local …

Binary image representation is essential format for document analysis. In general, different
available binarization techniques are implemented for different types of binarization …

Automatic text recognition from the natural images acquired in uncontrolled lighting
conditions is a challenging task due to the presence of shadows hindering the shape …

In the era of mobile imaging, the quality of document photos captured by smartphones often
suffers due to adverse lighting conditions. Traditional document analysis and optical …

Image binarization is still a challenging task in a variety of applications. In particular,
Document Image Binarization Contest (DIBCO) is organized regularly to track the state-of …

Image binarization is important step in the OCR (Optical Character Recognition). There are
several methods used for image binarization recently, but there is no way to select single or …

Convolutional neural networks (CNNs) have previously been broadly utilized to binarize
document images. These methods have problems when faced with degraded historical …

Binarization is a well-known image processing task, whose objective is to separate the
foreground of an image from the background. One of the many tasks for which it is useful is …