Text in natural scene images plays a vital role in scene understanding. It contains a rich and
abundant amount of valuable semantic information useful in many applications such as …

A lot of research has been devoted to identity documents analysis and recognition on mobile
devices. However, no publicly available datasets designed for this particular problem …

In this paper, we introduce an “on the device” text line recognition framework that is
designed for mobile or embedded systems. We consider per-character segmentation as a …

The increasing portability of physical manuscripts to the digital environment makes it
common for systems to offer automatic mechanisms for offline Handwritten Text Recognition …

Document image classification plays a vital role in the document image processing system.
Thus it is of great importance to have a clear understanding of the state-of-the-art of the …

Document images are often degraded by various stains, significantly impacting their
readability and hindering downstream applications such as document digitization and …

Most digital libraries that provide user-friendly interfaces, enabling quick and intuitive access
to their resources, are based on Document Image Analysis and Recognition (DIAR) …

Current trends in image segmentation are to compute a hierarchy of image segmentations
from fine to coarse. A classical approach to obtain a single meaningful image partition from a …

Seamless integration of information from digital and paper documents is crucial for efficient
knowledge management. One convenient way to achieve this is to digitize a document from …

Air pollution has emerged as a universal concern across the globe affecting human health.
This increasing danger motivates the study of systems for predicting air pollutant severities …