DocumentCode :
2273472
Title :
Handwritten Kannada character recognition based on Kohonen Neural Network
Author :
Vishwaas, M. ; Arjun, M.M. ; Dinesh, R.
Author_Institution :
JSSATE, Bangalore, India
fYear :
2012
fDate :
25-27 April 2012
Firstpage :
91
Lastpage :
97
Abstract :
In general, Online Handwriting Recognition refers to the dynamic movement of a Digitized pen on touchpad which simply involves collection of a sequence of x-yco-ordinates used to describe the online handwriting data. This paper presents a novel approach for online handwriting recognition of Kannada characters by combining Direction based Stroke Density principle(DSD) with Kohonen Neural Network (KNN). DSD principle forms the basis for feature selection whereas the subsequent Classification stage is carried out by KNN. The proposed method has been tested for 49 characters and 10 numerals of Kannada Language with 20 different handwritings resulting in an accuracy of 94.4%. This method is simple to implement and realize, also it is computationally efficient.
Keywords :
feature extraction; handwriting recognition; interactive devices; natural language processing; self-organising feature maps; DSD principle; KNN; Kannada language; Kohonen neural network; digitized pen; direction based stroke density principle; feature selection; handwritten Kannada character recognition; online handwriting data; online handwriting recognition; touchpad; x-y coordinate sequence collection; Character recognition; Equations; Handwriting recognition; Mathematical model; Neurons; Training; Vectors; Direction based Stroke density principle; Kannada Characters; Kohonen neural network; OCR; Online Handwriting recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Recent Advances in Computing and Software Systems (RACSS), 2012 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4673-0252-4
Type :
conf
DOI :
10.1109/RACSS.2012.6212704
Filename :
6212704
Link To Document :
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