International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 69 - Number 13 |
Year of Publication: 2013 |
Authors: Prachi Solanki, Malay Bhatt |
10.5120/11905-7982 |
Prachi Solanki, Malay Bhatt . Printed Gujarati Script OCR using Hopfield Neural Network. International Journal of Computer Applications. 69, 13 ( May 2013), 33-37. DOI=10.5120/11905-7982
Optical 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.