Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.imavis.2006.02.008
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dc.titleA partition approach for the restoration of camera images of planar and curled document
dc.contributor.authorLu, S.
dc.contributor.authorChen, B.M.
dc.contributor.authorKo, C.C.
dc.date.accessioned2013-07-23T09:25:18Z
dc.date.available2013-07-23T09:25:18Z
dc.date.issued2006
dc.identifier.citationLu, S., Chen, B.M., Ko, C.C. (2006). A partition approach for the restoration of camera images of planar and curled document. Image and Vision Computing 24 (8) : 837-848. ScholarBank@NUS Repository. https://doi.org/10.1016/j.imavis.2006.02.008
dc.identifier.issn02628856
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/43113
dc.description.abstractAs camera resolution increases, high-speed non-contact text capture through a digital camera is opening up a new channel for text capture and understanding. Unfortunately, the captured document images are normally coupled with the perspective and geometric distortions that cannot be handled by the existing optical character recognition (OCR) systems. In this paper, we propose a new technique, which is capable of removing the perspective and geometric distortions, and reconstructing the fronto-parallel view of text with a single document image. Different from reported approaches in the literature, the restoration of the distorted camera documents is carried out through the image partition, which divides the documents into multiple small image patches where text can be approximated to lie on a planar surface. The global distortion is thus corrected through the local rectification of the partitioned image patches one by one. Experimental results show that the proposed method is fast and easy for implementation. © 2006 Elsevier B.V. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.imavis.2006.02.008
dc.sourceScopus
dc.subjectDocument image analysis
dc.subjectDocument image rectification
dc.subjectFuzzy sets
dc.subjectMorphological image processing
dc.subjectOptical character recognition
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1016/j.imavis.2006.02.008
dc.description.sourcetitleImage and Vision Computing
dc.description.volume24
dc.description.issue8
dc.description.page837-848
dc.description.codenIVCOD
dc.identifier.isiut000240381100005
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