In India, more than 300 million people use Devanagari script for documentation. There has
been a significant improvement in the research related to the recognition of printed as well …

Hindi is the most widely spoken language in India, with more than 300 million speakers. As
there is no separation between the characters of texts written in Hindi as there is in English …

This paper is step to locate the researchers, their track in the way for recognizing the
characters from various regional scripts in India. This survey paper would provide a path for …

Challenges in OCR of Devanagari documents Page 1 Challenges in OCR of Dev anagari
Documents Suryaprakash Kompalli Sankalp Nayak Srirangaraj Setlur Venu Govindaraju …

Implications of technical demands made within digital libraries (DL's) for document image
analysis systems are discussed. The state-of-the-art is summarized, including a digest of …

This paper describes a novel recognition driven segmentation methodology for Devanagari
Optical Character Recognition. Prior approaches have used sequential rules to segment …

A large annotated corpus is critical to the development of robust optical character
recognizers (OCRs). However, creation of annotated corpora is a tedious task. It is laborious …

We outline two different techniques for OCR of machine printed, multi-font Devanagari text.
In the first design, words are segmented along linear boundaries. Subsequently …

Long Short-Term Memory (LSTM) networks are a suitable candidate for segmentation-free
Optical Character Recognition (OCR) tasks due to their good context-aware processing. In …

An image of real world is processed to identify blocks as candidates to be recognized. Each
block is subdivided into Sub-blocks, and each Sub-block is traversed to obtain counts, OO in …