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AuthorAkbari, Younes
AuthorKunhoth, Jayakanth
AuthorElharrouss, Omar
AuthorAl-Maadeed, Somaya
AuthorAbualsaud, Khalid
AuthorMohamed, Amr
AuthorKhattab, Tamer
Available date2024-03-26T11:56:47Z
Publication Date2023
Publication Name2023 International Symposium on Networks, Computers and Communications, ISNCC 2023
ResourceScopus
URIhttp://dx.doi.org/10.1109/ISNCC58260.2023.10323921
URIhttp://hdl.handle.net/10576/53522
AbstractThis paper introduces a database of multi-script (Arabic and English) for indoor scene text detection, taken from different angle-of-view. This database can be used in a variety of real-world applications, such as image search, robot navigation, and assisting the visually impaired. The database contains 944 images taken with smartphones in an indoor environment at Qatar University. These images were taken from at least three angles, making the database even more challenging. To evaluate the database, an OCR method based on multiple language detection is considered. The results show that multi-language detection should be given more attention in practice. The database is publicly available. https:/www.dropbox.com/s/7s7f936y4etzsu7/QU-door-dataset%20%282%29.zip?dl=0.
SponsorThis research work was made possible by research grant support (QUEX-CENG-SCDL-19/20-1) from Supreme Committee for Delivery and Legacy (SC) in Qatar.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectDatabase
Multi-lingual scene text
OCR
TitleIndoor Multi-Lingual Scene Text Database with Different Views
TypeConference Paper


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