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Cited 11 time in webofscience Cited 11 time in scopus
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dc.contributor.authorChoi, S-
dc.contributor.authorYun, JP-
dc.contributor.authorKoo, K-
dc.contributor.authorKim, SW-
dc.date.accessioned2016-03-31T08:49:46Z-
dc.date.available2016-03-31T08:49:46Z-
dc.date.created2013-02-08-
dc.date.issued2012-07-
dc.identifier.issn0957-4174-
dc.identifier.other2012-OAK-0000026362-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/16135-
dc.description.abstractThis paper deals with algorithms for text localization and character segmentation in images for process automation in the steel-making industry. Each character which comprises slab identification numbers may be corrupted severely before it is captured by network cameras. Therefore, proper processing is required to localize the target texts successfully. In this paper, we propose (1) a method to evaluate the closeness of an edge patch to the form of a closed contour, (2) an edge inspection method to determine character colors and estimate font thickness, and (3) three reasonable binarization methods to increase the performance of the algorithm for the detection of the left and right boundaries of the text rectangle. The experimental results show that the proposed algorithms are reliable. (C) 2012 Elsevier Ltd. All rights reserved.-
dc.description.statementofresponsibilityX-
dc.languageEnglish-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.relation.isPartOfEXPERT SYSTEMS WITH APPLICATIONS-
dc.subjectText detection-
dc.subjectText localization-
dc.subjectText extraction-
dc.subjectText-finder-
dc.subjectCharacter location-
dc.subjectCharacter segmentation-
dc.subjectOptical character recognition (OCR)-
dc.subjectTEXT DETECTION-
dc.subjectVIDEO FRAMES-
dc.subjectSTROKE FILTER-
dc.subjectCOLOR IMAGES-
dc.subjectRECOGNITION-
dc.subjectALGORITHM-
dc.subjectLOCATION-
dc.subjectEDGE-
dc.titleLocalizing slab identification numbers in factory scene images-
dc.typeArticle-
dc.contributor.college창의IT융합공학과-
dc.identifier.doi10.1016/J.ESWA.2012.01.124-
dc.author.googleChoi, S-
dc.author.googleYun, JP-
dc.author.googleKoo, K-
dc.author.googleKim, SW-
dc.relation.volume39-
dc.relation.issue9-
dc.relation.startpage7621-
dc.relation.lastpage7636-
dc.contributor.id10055882-
dc.relation.journalEXPERT SYSTEMS WITH APPLICATIONS-
dc.relation.indexSCI급, SCOPUS 등재논문-
dc.collections.nameJournal Papers-
dc.type.rimsART-
dc.identifier.bibliographicCitationEXPERT SYSTEMS WITH APPLICATIONS, v.39, no.9, pp.7621 - 7636-
dc.identifier.wosid000303281600005-
dc.date.tcdate2019-01-01-
dc.citation.endPage7636-
dc.citation.number9-
dc.citation.startPage7621-
dc.citation.titleEXPERT SYSTEMS WITH APPLICATIONS-
dc.citation.volume39-
dc.contributor.affiliatedAuthorKim, SW-
dc.identifier.scopusid2-s2.0-84862779341-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.wostc8-
dc.description.scptc8*
dc.date.scptcdate2018-05-121*
dc.type.docTypeArticle-
dc.subject.keywordPlusTEXT DETECTION-
dc.subject.keywordPlusRECOGNITION-
dc.subject.keywordPlusLOCATION-
dc.subject.keywordPlusEDGE-
dc.subject.keywordAuthorText detection-
dc.subject.keywordAuthorText localization-
dc.subject.keywordAuthorText extraction-
dc.subject.keywordAuthorText-finder-
dc.subject.keywordAuthorCharacter location-
dc.subject.keywordAuthorCharacter segmentation-
dc.subject.keywordAuthorOptical character recognition (OCR)-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryOperations Research & Management Science-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaOperations Research & Management Science-

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김상우KIM, SANG WOO
Dept of Electrical Enginrg
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