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dc.contributor.authorHadian-Jazi, M.en
dc.contributor.authorBab-Hadiashar, A.en
dc.contributor.authorHoseinnezhad, R.en
dc.contributor.authorSuter, D.en
dc.identifier.citationImage Processing, Theory, Tools and Applications, 2015 / Jennane, R. (ed./s), pp.163-168en
dc.description.abstractHough Transform (HT) is commonly used to solve the line extraction problem. Although images are discretized at the onset, the Hough domain is continuous and in practice it has to be partitioned into cells. It has been suggested that the optimality of the size (resolution) of those cells would depend on the amount noise in the image. In this paper, we study the effect of discretization on the success of line detection where there are nearby lines and develop a theoretical foundation for the optimality of the Hough domain discretization for segmentation purposes. Experiments with real images show that our results are useful in practice for line detection applications.en
dc.description.statementofresponsibilityMarjan Hadian-Jazi, Alireza Bab-Hadiashar, Reza Hoseinnezhad, and David Suteren
dc.relation.ispartofseriesInternational Conference on Image Processing Theory Tools and Applicationsen
dc.rights© 2015 IEEEen
dc.subjectLine detection; Hough Transform; Cell Sizeen
dc.titleTheoretical analysis of hough transform optimal cell size: Segmentation of nearby linesen
dc.typeConference paperen
dc.contributor.conferenceIEEE International Conference on Image Processing Theory, Tools and Applications (IPTA) (10 Nov 2015 - 13 Nov 2015 : Orleans, France)en
pubs.library.collectionComputer Science publicationsen
dc.identifier.orcidSuter, D. [0000-0001-6306-3023]en
Appears in Collections:Computer Science publications

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