Classical and Fuzzy Differential Methods in Shape Analysis

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

    83 Downloads (Pure)

    Abstract

    This study considers four means of defining differential operators for extracting local aspects of shape in ill-specified environments: fuzzy differentiation as kernel smoothing; differentiation in the sense of weak or generalized derivatives; differentiation for fuzzy functions between normed spaces; and fuzzy differentiation for mappings between fuzzy manifolds. More consideration is given to the last, norm-free approach, which involves the notions of an abstract fuzzy topological vector space, fuzzy differentiation between fuzzy topological vector spaces, fuzzy atlases, and tangent vectors of fuzzy manifolds.
    Original languageEnglish
    Title of host publicationShape in Picture: Mathematical Description of Shape in Grey-level Images
    Place of PublicationBerlin
    PublisherSpringer Nature
    Pages319-332
    Number of pages14
    Publication statusPublished - 1994

    Fingerprint

    Dive into the research topics of 'Classical and Fuzzy Differential Methods in Shape Analysis'. Together they form a unique fingerprint.

    Cite this