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المؤلفAdamK.
المؤلفBaigA.
المؤلفAl-MaadeedS.
المؤلفBouridaneA.
المؤلفEl-MenshawyS.
تاريخ الإتاحة2019-10-03T10:50:03Z
تاريخ النشر2018
اسم المنشورInternational Journal on Document Analysis and Recognition
المصدرScopus
الرقم المعياري الدولي للكتاب14332833
معرّف المصادر الموحدhttp://dx.doi.org/10.1007/s10032-018-0312-3
معرّف المصادر الموحدhttp://hdl.handle.net/10576/12024
الملخصThe age of a historical manuscript can be an invaluable source of information for paleographers and historians. The process of automatic manuscript age detection has inherent complexities, which are compounded by the lack of suitable datasets for algorithm testing. This paper presents a dataset of historical handwritten Arabic manuscripts designed specifically to test state-of-the-art authorship and age detection algorithms. Qatar National Library has been the main source of manuscripts for this dataset while the remaining manuscripts are open source. The dataset consists of over 2000 images taken from various handwritten Arabic manuscripts spanning fourteen centuries. In addition, a sparse representation-based approach for dating historical Arabic manuscript is also proposed. There is lack of existing datasets that provide reliable writing date and author identity as metadata. KERTAS is a new dataset of historical documents that can help researchers, historians and paleographers to automatically date Arabic manuscripts more accurately and efficiently.
راعي المشروعFundingThispublicationwasmadepossiblebyNPRPGrant#NPRPNPRP7-442-1-082fromtheQatarNationalResearchFund(amemberofQatarFoundation).Thestatementsmadehereinaresolelytheresponsibilityoftheauthors.
اللغةen
الناشرSpringer Verlag
الموضوعClassification
Featureextraction
Historicaldocumentsdataset
Imageprocessing
العنوانKERTAS: dataset for automatic dating of ancient Arabic manuscripts
النوعArticle
الصفحات283-290
رقم العدد4
رقم المجلد21
dc.accessType Abstract Only


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