Please use this identifier to cite or link to this item: https://doi.org/10.1145/1284420.1284427
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dc.titleA system for understanding imaged infographics and its applications
dc.contributor.authorHuang, W.
dc.contributor.authorTan, C.L.
dc.date.accessioned2013-07-04T08:18:34Z
dc.date.available2013-07-04T08:18:34Z
dc.date.issued2007
dc.identifier.citationHuang, W.,Tan, C.L. (2007). A system for understanding imaged infographics and its applications. DocEng'07: Proceedings of the 2007 ACM Symposium on Document Engineering : 9-18. ScholarBank@NUS Repository. <a href="https://doi.org/10.1145/1284420.1284427" target="_blank">https://doi.org/10.1145/1284420.1284427</a>
dc.identifier.isbn9781595937766
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/41055
dc.description.abstractInformation graphics, or infographics, are visual representations of information, data or knowledge. Understanding of infographics in documents is a relatively new research problem, which becomes more challenging when infographics appear as raster images. This paper describes technical details and practical applications of the system we built for recognizing and understanding imaged infographics located in document pages. To recognize infographics in raster form, both graphical symbol extraction and text recognition need to be performed. The two kinds of information are then auto-associated to capture and store the semantic information carried by the infographics. Two practical applications of the system are introduced in this paper, including supplement to traditional optical character recognition (OCR) system and providing enriched information for question answering (QA). To test the performance of our system, we conducted experiments using a collection of downloaded and scanned infographic images. Another set of scanned document pages from the University of Washington document image database were used to demonstrate how the system output can be used by other applications. The results obtained confirm the practical value of the system. Copyright 2007 ACM.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1145/1284420.1284427
dc.sourceScopus
dc.subjectApplications
dc.subjectAssociation of text and graphics
dc.subjectDocument image understanding
dc.subjectInfographics
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1145/1284420.1284427
dc.description.sourcetitleDocEng'07: Proceedings of the 2007 ACM Symposium on Document Engineering
dc.description.page9-18
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

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