Offline Handwritten Hindi SWARs Recognition using A Novel Wave based Feature Extraction Method
Offline handwritten character recognition is a very challenging area of research as handwriting of two persons may bear resemblance whereas handwriting of an individual may vary at different times. The character recognition accuracy depends on the ways the features are extracted from the samples and utilized to formulate the feature vector. In this paper, a novel technique TARANG for feature extraction is proposed to recognize offline handwritten Hindi SWARs (vowels). This technique for extracting features from an image is inspired by the natural movement of wave in a medium. A feature vector obtained by using proposed technique is used for the training of Backpropagation Neural Network and recognition rate as high as 96.2% is achieved.
Keywords: Offline Handwritten Character Recognition, Feature Extraction, Global Features, Local Features, Back-propagation Neural Network
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ABOUT THE AUTHORS
Ajay Indian
Ajay Indian received the M.C.A. degree in 2001 from Dr. B.R. Ambedkar University, Agra, India, and M.Tech. (Computer Science & Engineering) in 2010 from Gautam Buddha Technical University, Lucknow, India. Currently, he is an Associate Professor at Department of Computer Science & Applications, Invertis University, Bareilly, India and a research scholar at Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar, India. His research interests include Image Processing, Artificial Neural Networks, and Data Mining.
Karamjit Bhatia
Karamjit Bhatia received M.Phil. degree in Computer Applications in 1988 from University of Roorkee (now IIT Roorkee), Roorkee, India and received Ph.D. (Computer Science) in 2001 from Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar, India. Currently, he is a Professor at Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar, India. His research interests include Distributed Systems, Image Processing, and Mobile Ad-hoc Networks. He has published over 40 research papers in International Journals of repute and National/ International conference proceedings. Five Ph.D. degrees have been awarded under his supervision.
Ajay Indian
Ajay Indian received the M.C.A. degree in 2001 from Dr. B.R. Ambedkar University, Agra, India, and M.Tech. (Computer Science & Engineering) in 2010 from Gautam Buddha Technical University, Lucknow, India. Currently, he is an Associate Professor at Department of Computer Science & Applications, Invertis University, Bareilly, India and a research scholar at Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar, India. His research interests include Image Processing, Artificial Neural Networks, and Data Mining.
Karamjit Bhatia
Karamjit Bhatia received M.Phil. degree in Computer Applications in 1988 from University of Roorkee (now IIT Roorkee), Roorkee, India and received Ph.D. (Computer Science) in 2001 from Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar, India. Currently, he is a Professor at Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar, India. His research interests include Distributed Systems, Image Processing, and Mobile Ad-hoc Networks. He has published over 40 research papers in International Journals of repute and National/ International conference proceedings. Five Ph.D. degrees have been awarded under his supervision.
