Survey on Handwritten Character Recognition using Artificial Neural Network

Author(s):

CinuGeorge , christian college of engineering and technology, oddanchatram, India; S.Podhumani, christian college of engineering and technology, oddanchatram, India; Reena k Monish, christian college of engineering and technology, oddanchatram, India; T.Pavithra, christian college of engineering and technology, oddanchatram, India

Keywords:

Handwritten character recognition, artificial neural network, Auto encoder, Restricted Boltzmann machine

Abstract:

Character recognition has defined a lot of attention in the field of pattern recognition due to its various applications. Many researches can be carried out for online characters. An offline handwritten alphabetical characters recognition system using artificial neural network (ANN) is described in this paper. Here handwritten character recognition is done for languages like Tamil, Malayalam and English. The recognition rate is varied for different languages. In this paper the techniques like auto encoder support vector machine is used for extracting the feature of the handwritten alphabets. Handwritten Character Recognition (HCR) is useful in bank-cheque processing, signature verification, handwritten postal adders resolution and many more. In coming days, character recognition system might serve as a key function to create paperless environment by digitizing and processing existing paper documents.

Other Details:

Manuscript Id	:	IJSTEV2I10068
Published in	:	Volume : 2, Issue : 10
Publication Date	:	01/05/2016
Page(s)	:	287-290

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