JUCS - Journal of Universal Computer Science 17(1): 94-106, doi: 10.3217/jucs-017-01-0094
Choice of Classifiers in Hierarchical Recognition of Online Handwritten Kannada and Tamil Aksharas
expand article infoVenkatesh Narasimha Murthy‡, Angarai Ganesan Ramakrishnan§
‡ Tata Consultancy Services Limited, Bangalore, India§ Indian Institute of Science, Bangalore, India

Corresponding author: Venkatesh Murthy ( venk.n@tcs.com )

© Venkatesh Murthy, Angarai Ramakrishnan.
This article is freely available under the J.UCS Open Content License.
Citation: Murthy VN, Ramakrishnan AG (2011) Choice of Classifiers in Hierarchical Recognition of Online Handwritten Kannada and Tamil Aksharas. JUCS - Journal of Universal Computer Science 17(1): 94-106. https://doi.org/10.3217/jucs-017-01-0094
Open Access
Abstract
In this paper, we propose a novel dexterous technique for fast and accurate recognition of online handwritten Kannada and Tamil characters. Based on the primary classifier output and prior knowledge, the best classifier is chosen from set of three classifiers for second stage classification. Prior knowledge is obtained through analysis of the confusion matrix of primary classifier which helped in identifying the multiple sets of confused characters. Further, studies were carried out to check the performance of secondary classifiers in disambiguating among the confusion sets. Using this technique we have achieved an average accuracy of 92.6% for Kannada characters on the MILE lab dataset and 90.2% for Tamil characters on the HP Labs dataset.
Keywords
handwritten character recognition, DTW, PCA, Hierarchical Classification, Kannada, Tamil