期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2018
卷号：9
期号：3
DOI：10.14569/IJACSA.2018.090351
出版社：Science and Information Society (SAI)
摘要：Improving the accuracy of Arabic text recognition in imagery requires a big modern dataset as data is the fuel for many modern machine learning models. This paper proposes a new dataset, called QTID, for Quran Text Image Dataset, the first Arabic dataset that includes Arabic marks. It consists of 309,720 different 192x64 annotated Arabic word images that contain 2,494,428 characters in total, which were taken from the Holy Quran. These finely annotated images were randomly divided into 90%, 5%, 5% sets for training, validation, and testing, respectively. In order to analyze QTID, a different dataset statistics were shown. Experimental evaluation shows that current best Arabic text recognition engines like Tesseract and ABBYY FineReader cannot work well with word images from the proposed dataset.
关键词：HDF5 dataset; Arabic script; Holy Quran text image; handwritten text recognition; Arabic OCR; text image datasets
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