Vast collections of documents available in image format need to be indexed for information
retrieval purposes. In this framework, word spotting is an alternative solution to optical …

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 …

Multi-modal large language models (LLMs) have shown remarkable performance in various
natural language processing tasks, including data extraction from documents. However, the …

Image binarization is the process of separation of pixel values into two groups, white as
background and black as foreground. Thresholding plays a major in binarization of images …

Segmentation of text from badly degraded document images is a very challenging task due
to the high inter/intra-variation between the document background and the foreground text of …

Surface cracks in concrete structures are critical indicators of structural damage and
durability. Manual visual inspection, the most commonly used method in practice, is …

This paper presents a novel iterative deep learning framework and applies it to document
enhancement and binarization. Unlike the traditional methods that predict the binary label of …

This paper presents a new document image binarization technique that segments the text
from badly degraded historical document images. The proposed technique makes use of the …

Adaptive binarization methods play a central role in document image processing. In this
work, an adaptive and parameterless generalization of Otsu's method is presented. The …

Document images often suffer from different types of degradation that renders the document
image binarization a challenging task. This paper presents a document image binarization …