Classification of Handwritten Ancient Tamil characters using Complex Extreme Learning Machine

dc.category	Journal Article
dc.contributor.author	Subashini, P
dc.date.accessioned	2017-03-29T00:19:46Z
dc.date.available	2017-03-29T00:19:46Z
dc.date.issued	2013
dc.department	Computer Science	en_US
dc.description.abstract	Classification is the problem o f identifying, to which set o f categories a new observation belongs, on the basis o f a training set whose category membership is known. The process o f handwritten script classification involves extraction o f some defined characteristics calledfeatures to classify an unknown handwritten character into one o f the known classes. Zernike moments and regional features are extracted from the Tamil characters and they are formed as feature vectors. Complex Extreme Learning Machine is used to classify the handwritten ancient Tamil characters. Complex Extreme Learning Machine is trained with feature vectors. From the experimental result it is observed that the classifier when trained by combining Zernike moments with regional features gives a highest classification accuracy o f82.63%.	en_US
dc.identifier.uri	https://ir.avinuty.ac.in/handle/avu/2266
dc.lang	English	en_US
dc.publisher.name	International Journal of Emerging Technologies in Computational and Applied Sciences	en_US
dc.publisher.type	International	en_US
dc.title	Classification of Handwritten Ancient Tamil characters using Complex Extreme Learning Machine	en_US

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