Subjective and objective quality assessment of degraded document images.
The huge amount of degraded documents stored in libraries and archives around the world needs automatic procedures of enhancement, classification, transliteration, etc. While high-quality images of these documents are in general easy to be captured, the amount of damage these documents contain befor...
| Published in: | Journal of Cultural Heritage Vol. 30; pp. 199 - 210 |
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| Main Authors: | , , , |
| Format: | Article |
| Published: |
Elsevier B.V.
Mar2018
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=128303932&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 128303932 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 12962074 KK8 jtl: Journal of Cultural Heritage issn: 12962074 maglogo: N pubinfo: dt: Mar2018 vid: 30 pid: 467 pub: Elsevier B.V. artinfo: ui: 128303932 10.1016/j.culher.2017.10.001 ppf: 199 ppct: 11 formats: tig: atl: Subjective and objective quality assessment of degraded document images. aug: au: Shahkolaei, Atena Nafchi, Hossein Ziaei Al-Maadeed, Somaya Cheriet, Mohamed affil: Synchromedia Laboratory for Multimedia Communication in Telepresence, École de technologie supérieure, Montreal, QC H3C 1K3, Canada Department of Computer Science & Engineering, Qatar University, Doha, Qatar su: Transliteration Heritage tourism Preservation of cultural property Color image processing High resolution imaging sug: subj: Transliteration Heritage tourism Preservation of cultural property Color image processing High resolution imaging keyword: Degraded document images Document image quality assessment Human visual system log-Gabor filter MSCN coefficients Physical noises ab: The huge amount of degraded documents stored in libraries and archives around the world needs automatic procedures of enhancement, classification, transliteration, etc. While high-quality images of these documents are in general easy to be captured, the amount of damage these documents contain before imaging is unknown. It is highly desirable to measure the severity of degradation that each document image contains. The degradation assessment can be used in tuning parameters of processing algorithms, selecting the proper algorithm, finding damaged or exceptional documents, among other applications. In this paper, the first dataset of degraded document images along with the human opinion scores for each document image is introduced in order to evaluate the image quality assessment metrics on historical document images. In this research, human judgments on the overall quality of the document image are used instead of the previously used OCR performance. Also, we propose an objective no reference quality metric based on the statistics of the mean subtracted contrast normalized (MSCN) coefficients computed from segmented layers of each document image. The segmentation into four layers of foreground and background is done on the basis of an analysis of the log-Gabor filters. This segmentation is based on the assumption that the sensitivity of the human visual system (HVS) is different at the locations of text and non-text. Experimental results show that the proposed metric has comparable or better performance than the state-of-the-art metrics, while it has a moderate complexity. The developed dataset as well as the Matlab source code of the proposed metric is available at http://www.synchromedia.ca/system/files/VDIQA.zip . pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2018 holdings: @attributes: islocal: N |
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