........................................................................................................................ i Acknowledgements ...................................................................................................... ii Table of

Camera-based character recognition has a possibility to realize a variety of applications and has been paid attention. However, character images are often taken from different angles and characters tend to be distorted. In such a case, recognition accuracy becomes worse. Therefore, we must find some methods to deal with this problem. In this paper, we experimentally evaluate some affine-invaria...

Recognition of variously deformed character patterns is a salient subject for off-line hand-printed character recognition. Sufficient recognition performance for practical use has not been achieved despite reports of many recognition techniques. Our research examines effective recognition techniques for deformed characters, extending conventional recognition techniques using an on-line characte...

Odia is one of the oldest and popular languages of India, spoken by more than 44 million people, especially in Odisha, India. Some characters in Odia are made up of more than one connected symbols. Compound characters are written by associating modifiers with consonants, resulting in a huge number of possible combinations, running into hundreds of thousands. Therefore, systems developed for rec...

This paper describes two implementations in optical character recognition using template matching method and feature extraction method followed by support vector machine classification. With proper image preprocessing, the texts are segmented into isolated characters and the correlations between a single character and a given set of templates are computed to find the similarities and then ident...

In this paper, we present a new neural network (NN) based method for optical character recognition (OCR) as well as handwritten character recognition (HCR). Experimental results show that our proposed method achieves increased accuracy in optical character recognition as well as handwritten character recognition. We present through an overview of existing handwritten character recognition techn...

In this paper we present the GRUHD database of Greek characters, text, digits, and other symbols in unconstrained handwriting mode. The database consists of 1,760 forms that contain 667,583 handwritten symbols and 102,692 words in total, written by 1,000 writers, 500 men and equal number of women. Special attention was paid in gathering data from writers of different age and educational level. ...