Off-line handwritten character recognition using Hidden Markov Model

In this paper, we are presenting a method for the recognition of Malayalam handwritten vowels using Hidden Markov Model (HMM). OCR is a method to detect characters in different sources. The goal of OCR is to classify optical patterns in an image to the corresponding characters. Recognition of handwr...

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Bibliographic Details
Published inICACCI : 2014 International Conference on Advances in Computing, Communications and Informatics : 24-27 September 2014 pp. 518 - 523
Main Authors Gayathri, P., Ayyappan, Sonal
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2014
Subjects
Binarization
Character recognition
Feature extraction
Handwritten character recognition
Hidden Markov Model
Hidden Markov models
Image recognition
Markov processes
Normalization
Optical Character Recognition
Optical character recognition software
Pre-processing
Prototypes
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ISBN1479930784
9781479930784
DOI10.1109/ICACCI.2014.6968488

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Summary:In this paper, we are presenting a method for the recognition of Malayalam handwritten vowels using Hidden Markov Model (HMM). OCR is a method to detect characters in different sources. The goal of OCR is to classify optical patterns in an image to the corresponding characters. Recognition of handwritten Malayalam vowels is proposed in this paper. Images of the characters written by eighteen subjects are used for this experiment. Training and recognition are performed using Hidden Markov Model Toolkit. Recognition process involves several steps including image acquisition, dataset preparation, pre-processing, feature extraction, training and recognition. An average accuracy of about 81.38% has been obtained.
ISBN:1479930784
9781479930784
DOI:10.1109/ICACCI.2014.6968488