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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/15813
Title: Handwritten text recognition in Odia script using Hidden Markov Model
Authors: Bhoi S.
Dogra D.P.
Pratim Roy, Partha
Published in: Proceedings of 2015 5th National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics, NCVPRIPG 2015
Abstract: This paper presents a system for unconstrained handwritten Odia text recognition using Hidden Markov Model (HMM) framework. Existing literature for Odia text recognition works primarily with individual isolated characters. In this study we introduce a Odia dataset of word samples collected from different professionals. Concavity feature from each word image is extracted in our approach. Next, the features are fed to HMM-based sequential classifier for recognition. The experiment has been performed on a large dataset consisting of 4000 words and results obtained are encouraging. © 2015 IEEE.
Citation: Proceedings of 2015 5th National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics, NCVPRIPG 2015, (2016)
URI: https://doi.org/10.1109/NCVPRIPG.2015.7490014
http://repository.iitr.ac.in/handle/123456789/15813
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers Inc.
Keywords: Computer vision
Hidden Markov models
Image processing
Markov processes
Pattern recognition
Hand-written text recognition
HMM-based
Large dataset
Sequential classifier
Text recognition
Word images
Character recognition
ISBN: 9.78147E+12
Author Scopus IDs: 57190384663
35408975400
56880478500
Author Affiliations: Bhoi, S., School of Electrical Sciences, Indian Institute of Technology, Bhubaneswar, 751013, India
Dogra, D.P., School of Electrical Sciences, Indian Institute of Technology, Bhubaneswar, 751013, India
Roy, P.P., Department of Computer Science and Engineering, Indian Institute of Technology, Roorkee, India
Appears in Collections:Conference Publications [CS]

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