Abstract
Character Recognition (OCR) systems have been developed for the recognition of printed characters of non- Indian languages effectively. Efforts are going on for development of efficient OCR systems for Indian languages, especially for Gujarati, a popular language of west India. In this paper, an OCR system is developed for the recognition of basic characters in printed Gujarati text. To extract the features of printed Guajarati characters principal component analysis (PCA) is used. Hopfield Neural classifier has been effectively used for the classification of characters based on features. The system methodology can be extended for the recognition of other Indian languages. KeywordsCharacter Recognition (OCR), Gujarati text, PCA, Hopfield neural network.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
