Indoor Multi-Lingual Scene Text Database with Different Views
Author | Akbari, Younes |
Author | Kunhoth, Jayakanth |
Author | Elharrouss, Omar |
Author | Al-Maadeed, Somaya |
Author | Abualsaud, Khalid |
Author | Mohamed, Amr |
Author | Khattab, Tamer |
Available date | 2024-03-26T11:56:47Z |
Publication Date | 2023 |
Publication Name | 2023 International Symposium on Networks, Computers and Communications, ISNCC 2023 |
Resource | Scopus |
Abstract | This 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. |
Sponsor | This 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. |
Language | en |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Subject | Database Multi-lingual scene text OCR |
Type | Conference Paper |
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