Open AccessKANNADA CHARACTER RECOGNITION SYSTEM USING NEURAL NETWORK
Author(s) -
Suresh Kumar D S,
Ajay Kumar B R,
K. Chaitanya A.Kalyan
Publication year - 2012
Publication title -
international journal of computer and communication technology
Language(s) - English
Resource type - Journals
eISSN - 2231-0371
pISSN - 0975-7449
DOI - 10.47893/ijcct.2012.1142
Subject(s) - kannada , character (mathematics) , computer science , intelligent character recognition , artificial neural network , speech recognition , artificial intelligence , scripting language , optical character recognition , character encoding , intelligent word recognition , pattern recognition (psychology) , set (abstract data type) , reading (process) , character recognition , neocognitron , handwriting recognition , process (computing) , time delay neural network , feature extraction , image (mathematics) , linguistics , mathematics , geometry , philosophy , programming language , operating system
Handwriting recognition has been one of the active and challenging research areas in the field of pattern recognition. It has numerous applications which include, reading aid for blind, bank cheques and conversion of any hand written document into structural text form[1]. As there are no sufficient number of works on Indian language character recognition especially Kannada script among 15 major scripts in India[2].In this paper an attempt is made to recognize handwritten Kannada characters using Feed Forward neural networks. A handwritten kannada character is resized into 20x30 pixel.The resized character is used for training the neural network. Once the training process is completed the same character is given as input to the neural network with different set of neurons in hidden layer and their recognition accuracy rate for different kannada characters has been calculated and compared. The results show that the proposed system yields good recognition accuracy rates comparable to that of other handwritten character recognition systems.