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Recognition of Offline Handwritten Hindi Text Using SVM
Naresh Kumar Garg, Dr. Lakhwinder Kaur, Dr. Manish Jindal
Pages - 395 - 401     |    Revised - 15-08-2013     |    Published - 15-09-2013
Volume - 7   Issue - 4    |    Publication Date - September 2013  Table of Contents
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KEYWORDS
Handwritten Hindi Text, Segmentation, Shape Based Features, Recognition Rate, SVM Classifier.
ABSTRACT
Handwritten Hindi text recognition is emerging areas of research in the field of optical character recognition. In this paper, a segmentation based approach is used to recognize the text. The offline handwritten text is segmented into lines, lines into words and words into character for recognition. Shape features are extracted from the characters and fed into SVM classifier for recognition. The results obtained with the proposed feature set using SVM classifier is very challenging.
CITED BY (3)  
1 Singh, G., & Sachan, M. (2015, September). Offline Gurmukhi script recognition using knowledge based approach & Multi-Layered Perceptron neural network. In Signal Processing, Computing and Control (ISPCC), 2015 International Conference on (pp. 266-271). IEEE.
2 Garg, N. K., Kaur, L., & Jndal, M. (2015, June). Recognition of Offline Handwritten Hindi text using middle zone of the words. In Computer and Information Science (ICIS), 2015 IEEE/ACIS 14th International Conference on (pp. 325-328). IEEE.
3 Singh, G., & Sachan, M. (2014, December). Multi-layer perceptron (MLP) neural network technique for offline handwritten Gurmukhi character recognition. In Computational Intelligence and Computing Research (ICCIC), 2014 IEEE International Conference on (pp. 1-5). IEEE.
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Dr. Naresh Kumar Garg
GZSPTU Campus, CSE Department Bathinda-151001 - India
naresh2834@rediffmail.com
Dr. Dr. Lakhwinder Kaur
UCOE, Punjabi University, Patiala - India
Dr. Dr. Manish Jindal
Punjab University Regional Centre, Muktsar - India