CFP last date
20 May 2024
Reseach Article

Offline Handwritten Devanagari Vowels Recognition using KNN Classifier

by Rakesh Rathi, Ravi Krishan Pandey, Mahesh Jangid, Vikas Chaturvedi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 49 - Number 23
Year of Publication: 2012
Authors: Rakesh Rathi, Ravi Krishan Pandey, Mahesh Jangid, Vikas Chaturvedi
10.5120/7942-1270

Rakesh Rathi, Ravi Krishan Pandey, Mahesh Jangid, Vikas Chaturvedi . Offline Handwritten Devanagari Vowels Recognition using KNN Classifier. International Journal of Computer Applications. 49, 23 ( July 2012), 11-16. DOI=10.5120/7942-1270

@article{ 10.5120/7942-1270,
author = { Rakesh Rathi, Ravi Krishan Pandey, Mahesh Jangid, Vikas Chaturvedi },
title = { Offline Handwritten Devanagari Vowels Recognition using KNN Classifier },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 49 },
number = { 23 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 11-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume49/number23/7942-1270/ },
doi = { 10.5120/7942-1270 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:46:57.911108+05:30
%A Rakesh Rathi
%A Ravi Krishan Pandey
%A Mahesh Jangid
%A Vikas Chaturvedi
%T Offline Handwritten Devanagari Vowels Recognition using KNN Classifier
%J International Journal of Computer Applications
%@ 0975-8887
%V 49
%N 23
%P 11-16
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The discussion in the paper is regarding to the recognition of handwritten Devanagari vowels by means of a classifier named as K-NN (K- Nearest Neighbour). Before applying classifier, feature extortion is accomplished for extracting the feature points (FP) i. e. also known as division points (DP). In this paper the feature extortion is perform through recursive sub division technique, which is first time implemented on Devanagari vowels. K-NN classifier is functioned for the learning and the testing phases, through which the recognition go ahead to the high performances in terms of recognition rate, pre-processing and classification speed. Authors tested the described approach using the ISI (Indian Statistical Institute), Kolkata's handwritten Devanagari vowels database containing 9191 samples, which is divided into 1:3 as testing and training samples respectively. In the recognition process using K-NN classifier 88 vowels are total wrongly identified out of 2281vowels. The recognition rate comes out to be 96. 14%.

References
  1. Bremner D, Demaine E, Erickson J, Iacono J, Langerman S, Morin P, Toussaint G"Output-sensitive algorithms for computing nearest-neighbor decision boundaries". Discrete and Computational Geometry 33 (4): pp. 593–604, 2005.
  2. Nigsch F, Bender A, van Buuren B, Tissen J, Nigsch E, Mitchell JB, "Melting point prediction employing k-nearest neighbor algorithms and genetic parameter optimization" Journal of Chemical Information and Modeling 46 (6): pp. 2412–2422, 2006.
  3. Hall P, Park BU, Samworth RJ, "Choice of neighbor order in nearest-neighbor classification". Annals of Statistics 36 (5): pp. 2135–2152, 2008.
  4. U. Pal, T. Wakabayashi, F. Kimura, "Comparative Study of Devanagari Handwritten Character Recognition using Different Feature and Classifiers", 10th Intl. Conf. on Document Analysis and Recognition, pp. 1111-1115, 2009.
  5. R. Jayadevan, S. R. Kolhe, P. M. Patil, U. Pal, "Database development and recognition of handwritten devanagari legal amount words" Conference Proceeding: 10/2011;DOI:10. 1109/ICDAR. 2011. 69 In proceeding of: 2011 International conference on Document Analysis and Recognition (ICDAR),
  6. Reena Bajaj, LipikaDey ,SantanuChaudhury,"Devanagari Vowel recognition by combining decision of multiple connectionist classifiers", Sadhana Vol. 27,Part 1, pp. 59–72, February 2002.
  7. A. Elnagar and S. Harous, "Recognition of handwritten Hindi Vowels using structural descriptors," Journal of Experimental & Theoretical Artificial Intelligence, Vol. 15, no. 3,pp. 299–214, 2003
  8. R. J. Ramteke, S. C. Mehrotra, "Recognition of Handwritten Devnagari Vowels", International Journal of Computer Processing of Oriental Languages, 2008.
  9. N. Sharma, U. Pal, F. Kimura, and S. Pal, "Recognition of of?ine handwritten Devnagari characters using quadratic classi?er," in Proc. Indian Conference ComputerVision Graph. Image Process, pp. 805–816, 2006.
  10. C. V. Lakshmi, R. Jain, and C. Patvardhan, "Handwritten Devnagari Vowels recognition with higher accuracy," in Proc. International Conference Computer Intelligence Multimedia", pp. 255–259, 2007.
  11. M. Hanmandlu, A. V. Nath, A. C. Mishra, and V. K. Madasu, "Fuzzy model based recognition of handwritten hindi Vowels using bacterial foraging," in Proc. International Conference Computer Information Science,pp. 309–314, 2007.
  12. M. Hanmandlu, O. V. Ramana Murthy, Vamsi Krishna Madasu, "Fuzzy Model based recognition of handwritten Hindi characters", Digital Image Computing Techniques and Applications, pp. 7695-3067-IEEE. Feb-2007.
Index Terms

Computer Science
Information Sciences

Keywords

OHCR (Offline Handwritten Character Recognition) K-NN (K- Nearest Neighbor) Recursive Sub Division (A Feature Mining Technique)