Classification of Handwritten Ancient Tamil characters using Complex Extreme Learning Machine
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Date
2013
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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%.