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A Zone based Approach for Classification and Recognition of Telugu Handwritten Characters

Publication Type : Journal Article

Publisher : International Journal of Electrical and Computer Engineering.

Source : International Journal of Electrical and Computer Engineering, Volume 6, Issue 4, p.1647-1653 (2016)

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Keywords : K-nearest neighboring, Statistical features, Zoning

Campus : Mysuru

School : School of Arts and Sciences

Department : Computer Science

Year : 2016

Abstract : Realization of high accuracies and efficiencies in South Indian character recognition systems is one of the principle goals to be attempted time after time so as to promote the usage of optical character recognition (OCR) for South Indian languages like Telugu. The process of character recognition comprises pre-processing, segmentation, feature extraction, classification and recognition. The feature extraction stage is meant for uniquely recognizing each character image for the purpose of classifying it. The selection of a feature extraction algorithm is very critical and important for any image processing application and mostly of the times it is directly proportional to the type of the image objects that we have to identify. For optical technologies like South Indian OCR, the feature extraction technique plays a very vital role in accuracy of recognition due to the huge character sets. In this work we mainly focus on evaluating the performance of various feature extraction techniques with respect to Telugu character recognition systems and analyze its efficiencies and accuracies in recognition of Telugu character set. Copyright © 2016 Institute of Advanced Engineering and Science. All rights reserved.

Cite this Research Publication : N. Shoba Rani, Sanjay Kumar Verma, Anitta Joseph “A zone based approach for classification and recognition of telugu handwritten characters”, International Journal of Electrical and Computer Engineering, vol. 6, no. 4, pp. 1647-1653, 2016.

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