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Image registration in hough space using gradient of images

Shams, Ramtin; Barnes, Nick; Hartley, Richard

Description

We present an accurate and fast method for rigid registration of images with large non-overlapping areas using a Hough transformation of image gradients. The Hough space representation of gradients can be used to separate estimation of the rotation parameter from the translation. It also allows us to estimate transformation parameters for 2D images over a 1D space, hence reducing the computational complexity. The cost functions in the Hough domain have larger capture ranges compared to the cost...[Show more]

dc.contributor.authorShams, Ramtin
dc.contributor.authorBarnes, Nick
dc.contributor.authorHartley, Richard
dc.coverage.spatialAdelaide Australia
dc.date.accessioned2015-12-08T22:19:45Z
dc.date.createdDecember 3-5 2007
dc.identifier.isbn0769530672
dc.identifier.urihttp://hdl.handle.net/1885/31693
dc.description.abstractWe present an accurate and fast method for rigid registration of images with large non-overlapping areas using a Hough transformation of image gradients. The Hough space representation of gradients can be used to separate estimation of the rotation parameter from the translation. It also allows us to estimate transformation parameters for 2D images over a 1D space, hence reducing the computational complexity. The cost functions in the Hough domain have larger capture ranges compared to the cost functions in the intensity domain. This allows the optimization to converge better in the presence of large misalignments. We show that the combination of estimating registration parameters in the Hough domain and fine tuning the results in the intensity domain significantly improves performance of the application compared to the conventional intensity-based multi-resolution methods.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.relation.ispartofseriesDigital Image Computing: Techniques and Applications (DICTA 2007)
dc.sourceProceedings of the 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications
dc.source.urihttp://dicta2007.infoeng.flinders.edu.au/
dc.subjectKeywords: (algorithmic) complexity; (min ,max ,+) functions; 2D imaging; D space; Digital image computing; fine tuning; Hough spaces; hough transformation; image gradients; Intensity-based; Multiresolution (MR); Registration parameters; Rigid registration; Rotation
dc.titleImage registration in hough space using gradient of images
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2007
local.identifier.absfor080104 - Computer Vision
local.identifier.ariespublicationu4334215xPUB85
local.type.statusPublished Version
local.contributor.affiliationShams, Ramtin, College of Engineering and Computer Science, ANU
local.contributor.affiliationBarnes, Nick, College of Engineering and Computer Science, ANU
local.contributor.affiliationHartley, Richard, College of Engineering and Computer Science, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.startpage226
local.bibliographicCitation.lastpage232
local.identifier.doi10.1109/DICTA.2007.4426800
dc.date.updated2015-12-08T08:24:59Z
local.identifier.scopusID2-s2.0-44949184759
CollectionsANU Research Publications

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