BIROn - Birkbeck Institutional Research Online

    Fuzzy segmentation for object-based image classification

    Lizarazo, Ivan and Elsner, Paul (2009) Fuzzy segmentation for object-based image classification. International Journal of Remote Sensing 30 (6), pp. 1643-1649. ISSN 0143-1161.

    [img] Text
    8111.pdf - Published Version of Record
    Restricted to Repository staff only

    Download (1MB) | Request a copy


    This Letter proposes an object‐based image classification procedure which is based on fuzzy image‐regions instead of crisp image‐objects. The approach has three stages: (a) fuzzification in which fuzzy image‐regions are developed, resulting in a set of images whose digital values express the degree of membership of each pixel to target land‐cover classes; (b) feature analysis in which contextual properties of fuzzy image‐regions are quantified; and (c) defuzzification in which fuzzy image‐regions are allocated to target land‐cover classes. The proposed procedure is implemented using automated statistical techniques that require very little user interaction. The results indicate that fuzzy segmentation‐based methods produce acceptable thematic accuracy and could represent a viable alternative to current crisp image segmentation approaches.


    Item Type: Article
    School: Birkbeck Faculties and Schools > Faculty of Humanities and Social Sciences > School of Social Sciences
    Depositing User: Sarah Hall
    Date Deposited: 11 Sep 2013 16:02
    Last Modified: 02 Aug 2023 17:07


    Activity Overview
    6 month trend
    6 month trend

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item Edit/View Item