Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Skew estimation and correction for form documents using wavelet decomposition

Full metadata record
DC Field Value Language
dc.contributor.authorXi, DH-
dc.contributor.authorKamel, M-
dc.contributor.authorLee, SW-
dc.date.accessioned2021-09-09T06:58:31Z-
dc.date.available2021-09-09T06:58:31Z-
dc.date.created2021-06-19-
dc.date.issued2005-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/123274-
dc.description.abstractForm document image processing has become an increasingly essential technology in office automation tasks. One of the problems is that the document image may appear skewed for many reasons. Therefore, the skew estimation plays an important role in any automatic document analysis system. In the past few years, many algorithms have been developed to detect the skew angle of text document images. However, these algorithms suffer from two major deficiencies. Firstly, most of them suppose that the original image is monochrome and therefore they are not suitable to apply to documents with a complicated background. Secondly, most of the current methods were developed for general document images that are not as complicated as form documents. In this paper, we present a new approach to skew detection for grey-level form document images. In our system, image decomposition by 2D wavelet transformations is used to estimate the skew angle.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.titleSkew estimation and correction for form documents using wavelet decomposition-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, SW-
dc.identifier.wosid000233991100023-
dc.identifier.bibliographicCitationIMAGE ANALYSIS AND RECOGNITION, v.3656, pp.182 - 190-
dc.relation.isPartOfIMAGE ANALYSIS AND RECOGNITION-
dc.citation.titleIMAGE ANALYSIS AND RECOGNITION-
dc.citation.volume3656-
dc.citation.startPage182-
dc.citation.endPage190-
dc.type.rimsART-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaImaging Science & Photographic Technology-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.relation.journalWebOfScienceCategoryImaging Science & Photographic Technology-
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > Department of Artificial Intelligence > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Lee, Seong Whan photo

Lee, Seong Whan
인공지능학과
Read more

Altmetrics

Total Views & Downloads

BROWSE