Weighted distance mapping (WDM)

Egon van den Broek, N. Canagarajah (Editor), A. Chalmers (Editor), Theo E. Schouten, Peter M.F. Kisters, F. Deravi (Editor), S. Gibson (Editor), Harco C. Kuppens, P. Hobson (Editor), M. Mirmehdi (Editor), S. Marshall (Editor)

    Research output: Contribution to conferencePaperAcademic

    6 Citations (Scopus)
    21 Downloads (Pure)

    Abstract

    A new distance mapping technique is introduced: weighted distance mapping (WDM). It is based on an adapted version of Fast Exact Euclidean Distance (FEED) transforms. It computes, after assigning a metric, a probability space for partly categorized or clustered data. This is visualized by gradual intensity changes as illustrated by the categorization of a color space based on clustered data points. In addition, edge detection of boundaries between categories can be done to find exact borders of clusters or categories. Hence, Voronoi diagrams can be created. The proposed WDMs, with or without exact edges, provide a new rich source for data analysis as well as an intuitive method of describing structure in data.
    Original languageUndefined
    Pages157-164
    Number of pages8
    DOIs
    Publication statusPublished - 4 Apr 2005
    EventIEE International Conference on Visual Information Engineering, VIE 2005 - Glasgow, Scotland, UK
    Duration: 4 Apr 20056 Apr 2005

    Conference

    ConferenceIEE International Conference on Visual Information Engineering, VIE 2005
    Period4/04/056/04/05
    Other4-6 April 2005

    Keywords

    • HMI-VRG: Virtual Reality and Graphics
    • fast exact Euclidean distance
    • data clusters
    • data inspection
    • data point distance
    • data space description
    • data space visualization
    • EWI-21123
    • probability space
    • IR-79125
    • Data Analysis
    • FEED transform
    • Edge detection
    • Voronoi diagrams
    • Weighted distance mapping

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