research-article

Hindi handwritten word recognition using HMM and symbol tree

Authors:

Chetan Paulzagade,

Akash Deshmukh,

Kapil MehrotraAuthors Info & Claims

DAR '12: Proceeding of the workshop on Document Analysis and Recognition

Pages 9 - 14

https://doi.org/10.1145/2432553.2432556

Published: 16 December 2012 Publication History

Abstract

The proposed approach performs recognition of online handwritten isolated Hindi words using a combination of HMMs trained on Devanagari symbols and a tree formed by the multiple, possible sequences of recognized symbols.

In general, words in Indic languages are composed of a number of aksharas or syllables, which in turn are formed by groups of consonants and vowel modifiers. Segmentation of aksharas is critical to accurate recognition of both recognition primitives as well as the complete word. Also, recognition in itself is an intricate job. This holistic task of akshara segmentation, symbol identification and subsequent word recognition is targeted in our work. It is handled in an integrated segmentation-recognition framework. By making use of online stroke information for postulating symbol candidates and deriving HOG feature set from their image counterparts, the recognition becomes independent of stroke order and stroke shape variations. Thus, the system is well suited to unconstrained handwriting.

Data for this work is collected from different parts of India where Hindi language is predominantly in use. Symbols extracted from 60,000 words are used to train and test 140 symbol-HMM models. The system is designed to output one or more candidate words to the user, by tracing multiple tree paths (up to leaf nodes) under the condition that the symbol likelihood (confidence score) at every node is above threshold. Tests performed on 10,000 words yield an accuracy of 89%.

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Cited By

Singh HSharma RSingh V(2023)Language model based suggestions of next possible Gurmukhi character or word in online handwriting recognition systemMultimedia Tools and Applications10.1007/s11042-023-14654-082:30(47271-47289)Online publication date: 9-May-2023
https://doi.org/10.1007/s11042-023-14654-0
Gupta APurwar R(2021)Offline Handwritten Word Recognition of Devanagari Script2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)10.1109/ICAC3N53548.2021.9725477(1793-1798)Online publication date: 17-Dec-2021
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Hindi handwritten word recognition using HMM and symbol tree

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cover image ACM Other conferences

DAR '12: Proceeding of the workshop on Document Analysis and Recognition

December 2012

162 pages

ISBN:9781450317979

DOI:10.1145/2432553

Program Chairs:
A. G. Ramakrishnan
IISc, Bangalore
,
Sitaram Ramachandrula
HP Labs, Bangalore

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 16 December 2012

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DAR '12: Workshop on Document Analysis and Recognition

December 16, 2012

Mumbai, India

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Cited By

Singh HSharma RSingh V(2023)Language model based suggestions of next possible Gurmukhi character or word in online handwriting recognition systemMultimedia Tools and Applications10.1007/s11042-023-14654-082:30(47271-47289)Online publication date: 9-May-2023
https://doi.org/10.1007/s11042-023-14654-0
Gupta APurwar R(2021)Offline Handwritten Word Recognition of Devanagari Script2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)10.1109/ICAC3N53548.2021.9725477(1793-1798)Online publication date: 17-Dec-2021
https://doi.org/10.1109/ICAC3N53548.2021.9725477
Singh HSharma RSingh VKumar M(2021)Recognition of online handwritten Gurmukhi characters using recurrent neural network classifierSoft Computing10.1007/s00500-021-05620-9Online publication date: 10-Feb-2021
https://doi.org/10.1007/s00500-021-05620-9
Singh HSharma RSingh V(2020)Online handwriting recognition systems for Indic and non-Indic scripts: a reviewArtificial Intelligence Review10.1007/s10462-020-09886-7Online publication date: 8-Aug-2020
https://doi.org/10.1007/s10462-020-09886-7
Naik VDesai A(2019)Online Handwritten Gujarati Word RecognitionInternational Journal of Computer Vision and Image Processing10.4018/IJCVIP.20190101039:1(35-50)Online publication date: Jan-2019
https://doi.org/10.4018/IJCVIP.2019010103
Garg AJindal MSingh A(2019)Degraded offline handwritten Gurmukhi character recognition: study of various features and classifiersInternational Journal of Information Technology10.1007/s41870-019-00399-3Online publication date: 29-Nov-2019
https://doi.org/10.1007/s41870-019-00399-3
Narang SJindal MKumar M(2019)Devanagari ancient documents recognition using statistical feature extraction techniquesSādhanā10.1007/s12046-019-1126-944:6Online publication date: 13-May-2019
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YADAV MKR PURWAR RJAIN A(2018)Design of CNN architecture for Hindi CharactersADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal10.14201/ADCAIJ20187347627:3(47)Online publication date: 21-Sep-2018
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Yadav MPurwar R(2018)Integrating Wavelet Coefficients and CNN for Recognizing Handwritten Characters2018 2nd IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES)10.1109/ICPEICES.2018.8897291(1160-1164)Online publication date: Oct-2018
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Kumar MJindal MSharma RJindal S(2018)Character and numeral recognition for non-Indic and Indic scripts: a surveyArtificial Intelligence Review10.1007/s10462-017-9607-xOnline publication date: 3-Jan-2018
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