In this era of digitization, most hardcopy documents are being transformed into digital
formats. In the process of transformation, large quantities of documents are stored and …

There is a huge amount of historical documents in libraries and in various National Archives
that have not been exploited electronically. Although automatic reading of complete pages …

Despite decades of research, offline handwriting recognition (HWR) of degraded historical
documents remains a challenging problem, which if solved could greatly improve the …

Document image binarization is of great importance in the document image analysis and
recognition pipeline since it affects further stages of the recognition process. The evaluation …

In this paper a complete OCR methodology for recognizing historical documents, either
printed or handwritten without any knowledge of the font, is presented. This methodology …

Document image segmentation into text lines is one of the stages in unconstrained
handwritten document recognition. This paper presents a new algorithm for text line …

This paper introduces a new way for text-line extraction by integrating deep-learning based
pre-classification and state-of-the-art segmentation methods. Text-line extraction in complex …

Segmenting page images into text lines is a crucial pre-processing step for automated
reading of historical documents. Challenging issues in this open research field are given\eg …

We present a learning-free method for text line segmentation of historical handwritten
document images. This method relies on automatic scale selection together with second …

It is common for libraries to provide public access to historical and ancient document image
collections. It is common for such document images to require specialized processing in …