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AuthorShahkolaei A.
AuthorBeghdadi A.
AuthorAl-Maadeed S.
AuthorCheriet M.
Available date2020-03-03T06:19:01Z
Publication Date2018
Publication Name2nd IEEE International Workshop on Arabic and Derived Script Analysis and Recognition, ASAR 2018
ResourceScopus
URIhttp://dx.doi.org/10.1109/ASAR.2018.8480372
URIhttp://hdl.handle.net/10576/13069
AbstractIn this paper, a new dataset, called Multi-distortion Historical Document Image Database (MHDID), to be used for the research on quality assessment of degraded documents and degradation classification is proposed. The MHDID dataset contains 335 historical document images which are classified into four categories based on their distortion types, namely, paper translucency, stain, readers' annotations and worn holes. A total of 36 subjects participated to judge the quality of ancient document images. Pair comparison rating (PCR) is utilized as a subjective rating method for evaluating the visual quality of degraded document images. For each distortion image a mean opinion score (MOS) value is computed. This dataset could be used for evaluating the image quality assessment (IQA) measures as well as in the design of new metrics.
SponsorThis publication was made possible by NPRP grant NPRP 7-442-1-082 from the Qatar National Research Fund (a member of Qatar Foundation). The statements are solely the responsibility of the authors.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectHistorical document images
human visual system
image quality assessment
pair comparison rating
physical noises
TitleMHDID: A Multi-distortion Historical Document Image Database
TypeConference Paper
Pagination156 - 160
dc.accessType Abstract Only


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