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Extraction of reference lines and items from form document images with complicated background

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dc.contributor.authorXi, DH-
dc.contributor.authorLee, SW-
dc.date.accessioned2021-09-09T06:56:01Z-
dc.date.available2021-09-09T06:56:01Z-
dc.date.created2021-06-19-
dc.date.issued2005-02-
dc.identifier.issn0031-3203-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/123259-
dc.description.abstractThe extraction of reference lines and items is a fundamental and crucial task in form document analysis. Most of the studies performed so far were done in connection with binary images. This paper proposes a method of extracting lines from gray-level images, by constructing a 2D pseudo Gaussian-Coiflet wavelet with adjustable rectangular support. We also present a method of extracting items using the extracted reference lines and multiresolution wavelet sub-images, which is independent of the intensity of the strokes and backgrounds. The experimental results demonstrate the effectiveness of our proposed methods. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER SCI LTD-
dc.subjectORTHONORMAL BASES-
dc.subjectRECOGNITION-
dc.subjectALGORITHM-
dc.titleExtraction of reference lines and items from form document images with complicated background-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, SW-
dc.identifier.doi10.1016/j.patcog.2004.04.013-
dc.identifier.scopusid2-s2.0-6444226758-
dc.identifier.wosid000225349600012-
dc.identifier.bibliographicCitationPATTERN RECOGNITION, v.38, no.2, pp.289 - 305-
dc.relation.isPartOfPATTERN RECOGNITION-
dc.citation.titlePATTERN RECOGNITION-
dc.citation.volume38-
dc.citation.number2-
dc.citation.startPage289-
dc.citation.endPage305-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.subject.keywordPlusORTHONORMAL BASES-
dc.subject.keywordPlusRECOGNITION-
dc.subject.keywordPlusALGORITHM-
dc.subject.keywordAuthorform document analysis-
dc.subject.keywordAuthorreference line extraction-
dc.subject.keywordAuthoritem extraction-
dc.subject.keywordAuthorwavelet-
dc.subject.keywordAuthormultiresolution decomposition-
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