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Kannada, Telugu and Devanagari Handwritten Numeral Recognition with Probabilistic Neural Network: A Novel Approach

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RTIPPR
© 2010 by IJCA Journal
Number 2 - Article 5
Year of Publication: 2010
Authors:
B.V.Dhandra
R.G.Benne
Mallikarjun Hangarge

B.V.Dhandra, R.G.Benne and Mallikarjun Hangarge. Kannada, Telugu and Devanagari Handwritten Numeral Recognition with Probabilistic Neural Network:A Novel Approach. IJCA,Special Issue on RTIPPR (2):83–88, 2010. Published By Foundation of Computer Science. BibTeX

@article{key:article,
	author = {B.V.Dhandra and R.G.Benne and Mallikarjun Hangarge},
	title = {Kannada, Telugu and Devanagari Handwritten Numeral Recognition with Probabilistic Neural Network:A Novel Approach},
	journal = {IJCA,Special Issue on RTIPPR},
	year = {2010},
	number = {2},
	pages = {83--88},
	note = {Published By Foundation of Computer Science}
}

Abstract

In this paper, a novel approach for Kannada, Telugu and Devanagari handwritten numerals recognition based on global and local structural features is proposed. Probabilistic Neural Network (PNN) Classifier is used to classify the Kannada, Telugu and Devanagari numerals separately. Algorithm is validated with Kannada, Telugu and Devanagari numerals dataset by setting various radial values of PNN classifier under different experimental setup. The experimental results obtained are encouraging and comparable with other methods found in literature survey. The novelty of the proposed method is free from thinning and size normalization.

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