Curvature Estimation of Surfaces in 3D Grey-Value Images

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

    3 Citations (Scopus)

    Abstract

    In this paper we present a novel method to estimate curvature of iso grey-level surfaces in grey-value images. Our method succeeds where isophote curvature fails. There is neither a segmentation of the surface needed nor a parametric model assumed. Our estimator works on the orientation (normal vector) field of the surface. This orientation field and a description of local structure is obtained by the Gradient Structure Tensor. The estimated orientation field has discontinuities mod j. It is mapped via the Knutsson mapping to a continuous representation. The principal curvatures of the surface, a coordinate invariant property, are computed in this mapped representation. An evaluation shows that our curvature estimation is robust even in the presence of noise, independent of the scale of the object and furthermore the relative error stays small.
    Original languageUndefined/Unknown
    Title of host publicationICPR16, Proceedings
    EditorsR Kasturi, D Laurendeau, C Suen
    Place of PublicationLos Alamitos, CA
    PublisherIEEE
    Pages684-687
    Number of pages4
    ISBN (Print)0-7695-1696-3
    Publication statusPublished - 2002
    Event16th International Conference on Pattern Recognition (Quebec City, Canada), vol. II - Los Alamitos, CA
    Duration: 11 Aug 200215 Aug 2002

    Publication series

    Name
    PublisherIEEE Computer Society Press
    NameInternational Conference on Pattern Recognition
    Volume1
    ISSN (Print)1051-4651

    Conference

    Conference16th International Conference on Pattern Recognition (Quebec City, Canada), vol. II
    Period11/08/0215/08/02

    Bibliographical note

    ISSN 1051-4651, phpub 56

    Keywords

    • conference contrib. refereed
    • Conf.proc. > 3 pag

    Cite this