Please use this identifier to cite or link to this item:
https://doi.org/10.1145/1284420.1284427
DC Field | Value | |
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dc.title | A system for understanding imaged infographics and its applications | |
dc.contributor.author | Huang, W. | |
dc.contributor.author | Tan, C.L. | |
dc.date.accessioned | 2013-07-04T08:18:34Z | |
dc.date.available | 2013-07-04T08:18:34Z | |
dc.date.issued | 2007 | |
dc.identifier.citation | Huang, 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.isbn | 9781595937766 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/41055 | |
dc.description.abstract | Information 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.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1145/1284420.1284427 | |
dc.source | Scopus | |
dc.subject | Applications | |
dc.subject | Association of text and graphics | |
dc.subject | Document image understanding | |
dc.subject | Infographics | |
dc.type | Conference Paper | |
dc.contributor.department | COMPUTER SCIENCE | |
dc.description.doi | 10.1145/1284420.1284427 | |
dc.description.sourcetitle | DocEng'07: Proceedings of the 2007 ACM Symposium on Document Engineering | |
dc.description.page | 9-18 | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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