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A Survey of Contextual Handwritten Recognition Systems based HMMs for Cursive Arabic and Latin Script

by Mouhcine Rabi, Mustapha Amrouch, Zouhir Mahani
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 160 - Number 2
Year of Publication: 2017
Authors: Mouhcine Rabi, Mustapha Amrouch, Zouhir Mahani
10.5120/ijca2017912982

Mouhcine Rabi, Mustapha Amrouch, Zouhir Mahani . A Survey of Contextual Handwritten Recognition Systems based HMMs for Cursive Arabic and Latin Script. International Journal of Computer Applications. 160, 2 ( Feb 2017), 31-37. DOI=10.5120/ijca2017912982

@article{ 10.5120/ijca2017912982,
author = { Mouhcine Rabi, Mustapha Amrouch, Zouhir Mahani },
title = { A Survey of Contextual Handwritten Recognition Systems based HMMs for Cursive Arabic and Latin Script },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2017 },
volume = { 160 },
number = { 2 },
month = { Feb },
year = { 2017 },
issn = { 0975-8887 },
pages = { 31-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume160/number2/27048-2017912982/ },
doi = { 10.5120/ijca2017912982 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:05:35.067490+05:30
%A Mouhcine Rabi
%A Mustapha Amrouch
%A Zouhir Mahani
%T A Survey of Contextual Handwritten Recognition Systems based HMMs for Cursive Arabic and Latin Script
%J International Journal of Computer Applications
%@ 0975-8887
%V 160
%N 2
%P 31-37
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Offline handwriting recognition has become lately a very popular research area and the number of its possible application is very large. Most recognition system are based on modeling characters to recognize, then the concatenation of these models to recognize a word, while modeling character allows deformations related to its context. This paper provides a survey of handwritten recognition systems based on context-dependent character modeling to account possible deformations related to its context. It examines the literature on the most significant work in contextual handwritten text recognition for two different alphabets, Latin and Arabic. Finally discussing the comparative results to achieve a comprehensive summary of the various approaches and systems taking account the character’s context which could help open up some interesting new prospects.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Offline handwriting Recognition Latin Arabic Context Cursive

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