Word-Wise Tri-Lingual Script identification using K-NN and SVM

Authors(2) :-Renuka Devi B, Raghavendra Srinivas

This paper presents the script identification for tri-lingual based on K-NN and SVM classifier. For the proposed three languages were utilized namely: Kannada, Hindi and English. For the experiment 6000 word images dataset has been used it includes 2000 images belongs to each language. For the features LBP features are extracted from word images. The no. of features are 59 obtained from LBP method. For the recognition K-NN and SVM classifier has been used accuracy. The optimum result is for K-NN is 98.38% and for SVM 98.50% are obtained.

Authors and Affiliations

Renuka Devi B
Computer Science Department, JSS Manjunatheshwara Institute ofvUnder-Graduate and Post-Graduate Studies,Vidyagiri, Dharwad, Karnataka, India
Raghavendra Srinivas
Department of Computer Science, University of Horticultural Sciences, Bagalkot, Karnataka, India

Script identification, word wise images, Document Image, K-NN,SVM .

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Publication Details

Published in : Volume 2 | Issue 5 | September-October 2017
Date of Publication : 2017-10-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 601-603
Manuscript Number : CSEIT1725108
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Renuka Devi B, Raghavendra Srinivas, "Word-Wise Tri-Lingual Script identification using K-NN and SVM ", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 5, pp.601-603, September-October-2017.
Journal URL : http://ijsrcseit.com/CSEIT1725108

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