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dc.contributor.authorRezaei, S.B.
dc.contributor.authorShanbehzadeh, J.
dc.contributor.authorSarrafzadeh, Hossein
dc.contributor.editor-
dc.date.accessioned2017-07-20T22:56:04Z
dc.date.available2017-07-20T22:56:04Z
dc.date.issued2017-03
dc.identifier.isbn9789881404732
dc.identifier.issn2078-0958
dc.identifier.issn2078-0966
dc.identifier.urihttps://hdl.handle.net/10652/3869
dc.description.abstractThe skew of the scanned document image is inevitable, and its correction improves the performance of document recognition systems. Skew specifies the text lines deviation from the horizontal or vertical axes. To date, skew estimation algorithms have employed specific features in a repetitive process. We can improve these algorithms by simply using an adaptive algorithm. This approach is suitable when we have large number of similar documents. This paper proposes adaptive document image skew estimation algorithm using the features of existing methods and supervised learning. This approach significantly improves the skew estimation time and accuracy. The time improvement comes from the training that need be performed only once on the training images rather than the repetitive process for each image of previous algorithms. The accuracy improvement comes from the appropriate selection of features, learning algorithm and image adaptively. This method works well in all skew ranges up to 0.1°.en_NZ
dc.language.isoenen_NZ
dc.publisherInternational Association of Engineers (IAENG)en_NZ
dc.relation.urihttp://www.iaeng.org/publication/IMECS2017/IMECS2017_pp425-433.pdfen_NZ
dc.subjectscanned document imageen_NZ
dc.subjectskew estimation algorithmsen_NZ
dc.subjectsupervised learningen_NZ
dc.subjectdocument recognitionen_NZ
dc.titleAdaptive document image skew estimationen_NZ
dc.typeConference Contribution - Paper in Published Proceedingsen_NZ
dc.date.updated2017-05-12T14:30:02Z
dc.rights.holderAuthorsen_NZ
dc.subject.marsden0801 Artificial Intelligence and Image Processingen_NZ
dc.identifier.bibliographicCitationRezaei, S.B., Shanbehzadeh, J., & Sarrafzadeh, A. (2017, March). Adaptive document image skew estimation. - (Ed.), International MultiConference of Engineers and Computer Scientists 2017 (IMECS2017) 1, 423-433. http://www.iaeng.org/publication/IMECS2017/IMECS2017_pp425-433.pdfen_NZ
unitec.publication.spage425en_NZ
unitec.publication.lpage433en_NZ
unitec.publication.volume33en_NZ
unitec.publication.titleInternational MultiConference of Engineers and Computer Scientists 2017 (IMECS2017)en_NZ
unitec.conference.titleInternational MultiConference of Engineers and Computer Scientists 2017 (IMECS2017)en_NZ
unitec.conference.orgInternational Association of Engineers (IAENG)en_NZ
unitec.conference.locationHong Kong, Chinaen_NZ
unitec.conference.sdate2017-03-15
unitec.conference.edate2017-03-17
unitec.peerreviewedyesen_NZ
dc.contributor.affiliationUnitec Institute of Technologyen_NZ
dc.contributor.affiliationIran University of Science and Technologyen_NZ
dc.contributor.affiliationUniversity of Kharazmi (Tehran, Iran)en_NZ
unitec.identifier.roms59837en_NZ
unitec.institution.studyareaComputing


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