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 …

The character recognition system is a vital area in the field of pattern recognition. One
interesting, complex, and challenging task is handwritten character recognition because of …

The past few decades have witnessed an intensive research on optical character
recognition (OCR) for Roman, Chinese, and Japanese scripts. A lot of work has been also …

Computer vision is a very vast concept and a lot of researchers are inventing new ideas to
improve recognition accuracy for the machine. Today one can see driverless cars, automatic …

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 …

Standard convolution neural network (CNN) achieves high level of accuracy for the
recognition of characters in different languages. However, like other deep neural networks …

Hindi is the most prevalent language in India and is spoken by a large majority of the Indian
population. It also is one of the official languages of the country. The Hindi language is …

OCR for printed classical Indic documents written in Sanskrit is a challenging research
problem. It involves complexities such as image degradation, lack of datasets and long …

The optical character recognition (OCR) systems for Hindi language were the most primitive
ones and occupy a significant place in pattern recognition. The Hindi language OCR …

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