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Text information extraction in images and video: a survey

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dc.contributor.authorJung, K-
dc.contributor.authorKim, KI-
dc.contributor.authorJain, AK-
dc.date.available2018-05-10T18:04:45Z-
dc.date.created2018-04-17-
dc.date.issued2004-05-
dc.identifier.issn0031-3203-
dc.identifier.urihttp://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/19995-
dc.description.abstractText data present in images and video contain useful information for automatic annotation, indexing, and structuring of images. Extraction of this information involves detection, localization, tracking, extraction, enhancement, and recognition of the text from a given image. However, variations of text due to differences in size, style, orientation, and alignment, as well as low image contrast and complex background make the problem of automatic text extraction extremely challenging. While comprehensive surveys of related problems such as face detection, document analysis, and image & video indexing can be found, the problem of text information extraction is not well surveyed. A large number of techniques have been proposed to address this problem, and the purpose of this paper is to classify and review these algorithms, discuss benchmark data and performance evaluation, and to point out promising directions for future research. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.-
dc.publisherELSEVIER SCI LTD-
dc.relation.isPartOfPATTERN RECOGNITION-
dc.subjectSCENE IMAGES-
dc.subjectCOLOR DOCUMENTS-
dc.subjectLICENSE PLATES-
dc.subjectDIGITAL VIDEO-
dc.subjectRECOGNITION-
dc.subjectRETRIEVAL-
dc.subjectCHARACTERS-
dc.subjectLOCATION-
dc.subjectLOCALIZATION-
dc.subjectSEGMENTATION-
dc.titleText information extraction in images and video: a survey-
dc.typeArticle-
dc.identifier.doi10.1016/j.patcog.2003.10.012-
dc.type.rimsART-
dc.identifier.bibliographicCitationPATTERN RECOGNITION, v.37, no.5, pp.977 - 997-
dc.description.journalClass1-
dc.identifier.wosid000220677200010-
dc.citation.endPage997-
dc.citation.number5-
dc.citation.startPage977-
dc.citation.titlePATTERN RECOGNITION-
dc.citation.volume37-
dc.contributor.affiliatedAuthorJung, K-
dc.type.docTypeArticle-
dc.subject.keywordAuthortext information extraction-
dc.subject.keywordAuthortext detection-
dc.subject.keywordAuthortext localization-
dc.subject.keywordAuthortext tracking-
dc.subject.keywordAuthortext enhancement-
dc.subject.keywordAuthorOCR-
dc.subject.keywordPlusSCENE IMAGES-
dc.subject.keywordPlusCOLOR DOCUMENTS-
dc.subject.keywordPlusLICENSE PLATES-
dc.subject.keywordPlusDIGITAL VIDEO-
dc.subject.keywordPlusRECOGNITION-
dc.subject.keywordPlusRETRIEVAL-
dc.subject.keywordPlusCHARACTERS-
dc.subject.keywordPlusLOCATION-
dc.subject.keywordPlusLOCALIZATION-
dc.subject.keywordPlusSEGMENTATION-
dc.description.journalRegisteredClassscopus-
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