<div class="csl-bib-body">
<div class="csl-entry">Zaman, Q., Khusro, S., & Tjoa, A. M. (2023). Improved Detection and Interpretation of Multilingual Signboards in Natural Scene for Visually Impaired People. In <i>2023 IEEE International Conference on Data and Software Engineering (ICoDSE)</i> (pp. 126–131). IEEE. https://doi.org/10.1109/ICoDSE59534.2023.10291385</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/192937
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dc.description.abstract
Visually impaired individuals face numerous challenges in localization, navigation, reading content, and communicating with others. Unlike sighted individuals who rely on vision in the physical environment to reach their destinations, visually impaired individuals require assistive technologies and smartphone-based applications that employ computer vision to overcome the issues of obstacle detection, read signboards, and navigate in natural scenes. Signboards with text information serve as crucial indicators for navigation and recognition in daily life. However, detecting and interpreting signboard text in natural scenes poses difficulties for visually impaired individuals. Researchers have made efforts to address issues such as text detection on signboards, reducing blurriness, removing backgrounds, improving lighting conditions, and enhancing accuracy and response time of recognition. The primary challenges lie in the detection and interpretation of multilingual and diverse content on signboards in real-time. The proposed system presents a methodology for real-time detection and interpretation of diverse content on signboards, including text in English and Urdu along with phone numbers, for visually impaired individuals. An Android-based application is developed to improve text detection and recognition methods for multilingual texts, providing vital navigation information to visually impaired individuals in real-time. The methodology and application are evaluated, and the results demonstrate promising outcomes.
en
dc.language.iso
en
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dc.subject
Multilingual Text
en
dc.subject
Navigation Assistance
en
dc.subject
Signboard Detection
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dc.subject
Visually Impaired People
en
dc.title
Improved Detection and Interpretation of Multilingual Signboards in Natural Scene for Visually Impaired People
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.relation.publication
2023 IEEE International Conference on Data and Software Engineering (ICoDSE)
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dc.contributor.affiliation
Department of Computer Science University of Peshawar Peshawar, Pakistan
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dc.contributor.affiliation
Department of Computer Science University of Peshawar Peshawar, Pakistan
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dc.relation.isbn
979-8-3503-8138-2
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dc.relation.doi
10.1109/ICoDSE59534.2023
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dc.relation.issn
2640-0235
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dc.description.startpage
126
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dc.description.endpage
131
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dc.type.category
Full-Paper Contribution
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dc.relation.eissn
2640-0227
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tuw.booktitle
2023 IEEE International Conference on Data and Software Engineering (ICoDSE)
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tuw.peerreviewed
true
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tuw.relation.publisher
IEEE
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tuw.researchTopic.id
I4
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tuw.researchTopic.name
Information Systems Engineering
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E194-04 - Forschungsbereich Data Science
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tuw.publication.orgunit
E194-01 - Forschungsbereich Software Engineering
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tuw.publisher.doi
10.1109/ICoDSE59534.2023.10291385
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dc.description.numberOfPages
6
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tuw.author.orcid
0000-0001-7898-3156
-
tuw.author.orcid
0000-0002-8295-9252
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tuw.event.name
2023 IEEE International Conference on Data and Software Engineering (ICoDSE)
en
tuw.event.startdate
07-09-2023
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tuw.event.enddate
08-09-2023
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.place
Toba
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tuw.event.country
ID
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tuw.event.presenter
Zaman, Qamar
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tuw.event.presenter
Khusro, Shah
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tuw.event.presenter
Tjoa, A Min
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wb.sciencebranch
Informatik
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wb.sciencebranch
Wirtschaftswissenschaften
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
5020
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wb.sciencebranch.value
90
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wb.sciencebranch.value
10
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item.grantfulltext
none
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item.cerifentitytype
Publications
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item.openairecristype
http://purl.org/coar/resource_type/c_5794
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item.languageiso639-1
en
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item.openairetype
conference paper
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item.fulltext
no Fulltext
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crisitem.author.dept
Department of Computer Science University of Peshawar Peshawar, Pakistan
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crisitem.author.dept
Department of Computer Science University of Peshawar Peshawar, Pakistan
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crisitem.author.dept
E194-04 - Forschungsbereich E-Commerce
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crisitem.author.orcid
0000-0002-8295-9252
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crisitem.author.parentorg
E194 - Institut für Information Systems Engineering