Using hybrid knowledge engineering and image processing in color virtual restoration of ancient murals

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dc.contributor.author Pan, Yunhe
dc.contributor.author Liu, Yonghuai
dc.contributor.author Wei, Baogang
dc.date.accessioned 2008-01-23T12:50:13Z
dc.date.available 2008-01-23T12:50:13Z
dc.date.issued 2003-09
dc.identifier.citation Pan , Y , Liu , Y & Wei , B 2003 , ' Using hybrid knowledge engineering and image processing in color virtual restoration of ancient murals ' IEEE Transactions on Knowledge and Data Engineering , pp. 1338-1343 . , 10.1109/TKDE.2003.1232282 en
dc.identifier.other PURE: 75130
dc.identifier.other dspace: 2160/465
dc.identifier.uri http://hdl.handle.net/2160/465
dc.description IEEE Transactions on Knowledge and Data Engineering, vol. 15, no. 5, pp. 1338-1343, 2003. en
dc.description.abstract Abstract—This paper proposes a novel scheme to virtually restore the colors of ancient murals. Our approach integrates artificial intelligence techniques with digital image processing methods. The knowledge related to the mural colors is first categorized into four types. A hybrid frame and rule-based approach is then developed to represent knowledge and to infer colors. An algorithm that takes into account color similarity and spatial proximity is developed to segment mural images. A novel color transformation method based on color histograms is finally proposed to restore the colors of murals. A number of experiments based on real images have demonstrated the validity of the proposed scheme for color restoration. en
dc.format.extent 6 en
dc.language.iso eng
dc.relation.ispartof IEEE Transactions on Knowledge and Data Engineering en
dc.title Using hybrid knowledge engineering and image processing in color virtual restoration of ancient murals en
dc.type Text en
dc.type.publicationtype Article (Journal) en
dc.identifier.doi http://dx.doi.org/10.1109/TKDE.2003.1232282
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Vision, Graphics and Visualisation Group en
dc.description.status Peer reviewed en


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