Abstract: Offline Handwritten word Recognition (HWR) achieved increasing attention in the past few decades. Recognizing Indian language of Kannada is very difficult task not only because of variation in the handwriting, also because of number of alphabets present in Kannada languages, number of shapes, etc. To achieve the good recognition rate it is important to have good combination of feature extraction techniques and classifier. In this paper mainly we have used Gray Level Co-occurrence Matrix (GLCM) to extract the features and Support Vector Machines (SVM) for recognition. Experimental results show the good accuracy rate.
Keywords: Offline Handwritten Word Recognition (HWR), feature extraction, classifier, Gray Level Co-occurrence Matrix (GLCM), Support Vector Machines (SVM).
Title: Offline Kannada Handwritten Word Recognition Using Support Vector Machines (SVM)
Author: Rohith Kumar, M S Patel
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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