Classification and Recognition of Printed Hindi Characters Using Artificial Neural Networks
Автор: B.Indira,M.Shalini, M.V. Ramana Murthy, Mahaboob Sharief Shaik
Журнал: International Journal of Image, Graphics and Signal Processing(IJIGSP) @ijigsp
Статья в выпуске: 6 vol.4, 2012 года.
Бесплатный доступ
Character Recognition is one of the important tasks in Pattern Recognition. The complexity of the character recognition problem depends on the character set to be recognized. Neural Network is one of the most widely used and popular techniques for character recognition problem. This paper discusses the classification and recognition of printed Hindi Vowels and Consonants using Artificial Neural Networks. The vowels and consonants in Hindi characters can be divided in to sub groups based on certain significant characteristics. For each group, a separate network is designed and trained to recognize the characters which belong to that group. When a test character is given, appropriate neural network is invoked to recognize the character in that group, based on the features in that character. The accuracy of the network is analyzed by giving various test patterns to the system.
Pattern Recognition, Character Recognition, Artificial Neural Network, Feature extraction, Thinning
Короткий адрес: https://sciup.org/15012329
IDR: 15012329
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