Image registration in hough space using gradient of images

Ramtin Shams*, Nick Barnes, Richard Hartley

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    9 Citations (Scopus)

    Abstract

    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 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.

    Original languageEnglish
    Title of host publicationProceedings - Digital Image Computing Techniques and Applications
    Subtitle of host publication9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007
    Pages226-232
    Number of pages7
    DOIs
    Publication statusPublished - 2007
    EventAustralian Pattern Recognition Society (APRS) - Glenelg, SA, Australia
    Duration: 3 Dec 20075 Dec 2007

    Publication series

    NameProceedings - Digital Image Computing Techniques and Applications: 9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007

    Conference

    ConferenceAustralian Pattern Recognition Society (APRS)
    Country/TerritoryAustralia
    CityGlenelg, SA
    Period3/12/075/12/07

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