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المؤلفAkbari, Younes
المؤلفKunhoth, Jayakanth
المؤلفElharrouss, Omar
المؤلفAl-Maadeed, Somaya
المؤلفAbualsaud, Khalid
المؤلفMohamed, Amr
المؤلفKhattab, Tamer
تاريخ الإتاحة2024-03-26T11:56:47Z
تاريخ النشر2023
اسم المنشور2023 International Symposium on Networks, Computers and Communications, ISNCC 2023
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/ISNCC58260.2023.10323921
معرّف المصادر الموحدhttp://hdl.handle.net/10576/53522
الملخصThis 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.
راعي المشروعThis 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.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعDatabase
Multi-lingual scene text
OCR
العنوانIndoor Multi-Lingual Scene Text Database with Different Views
النوعConference Paper


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