This study aims to enhance handwritten text recognition (HTR) performance and domain
adaptability by combining an optical character recognition (OCR) model with a language …

The text lines of ancient Tibetan books are skewed and distorted, strokes are broken, and
complex adjacent text lines touch each other, which makes text line segmentation extremely …

The extraction of text lines from document images is a critical step in optical character
recognition. It is still considered an open document analysis problem. The presence of …

Document image processing is one of the growing research fields in the digital world for
applications like data base indexing, text recognition, signature verification, web-searching …

Text line segmentation is a necessary preliminary step before most text transcription
algorithms are applied. The leading deep learning networks used in this context (ARU-Net …

Abstract In Codice Ratio is a research project to study techniques for analyzing the contents
of historical documents conserved in the Vatican Apostolic Archives. In this paper, we …

Featured Application The proposed technique and the database created will be useful for
the development of an optical character recognition system for Malayalam handwritten …

Automatic handwriting recognition systems rely on text line segmentation. Text line
segmentation faces a number of obstacles, such as irregular text line gaps, slanted text …

The automatic localization of text lines is an important step in the analysis of handwritten
historical documents. It is a valuable tool for further analysis, such as studying handwriting …

The focus of this paper is offline handwriting Stroke Trajectory Recovery (STR), which
facilitates the tasks such as handwriting recognition and synthesis. The input is an image of …