Precise acquisition and unsupervised segmentation of multi-spectral images

David Delgado Gomez, Line Katrine Harder Clemmensen, Bjarne Kjær Ersbøll, Jens Michael Carstensen

    Research output: Contribution to journalJournal articleResearchpeer-review


    In this work, an integrated imaging system to obtain accurate and reproducible multi-spectral images and a novel multi-spectral image segmentation algorithm are proposed. The system collects up to 20 different spectral bands within a range that vary from 395 nm to 970 nm. The system is designed to acquire geometrically and chromatically corrected images in homogeneous and diffuse illumination, so images can be compared over time. The proposed segmentation algorithm combines the information provided by all the spectral bands to segment the different regions of interest. Three experiments are conducted to show the ability of the system to acquire highly precise, reproducible and standardized multi-spectral images and to show its applicabilities in different situations.
    Original languageEnglish
    JournalComputer Vision and Image Understanding
    Issue number2-3
    Pages (from-to)183-193
    Publication statusPublished - 2007


    • Exploratory data analysis
    • Pattern recognition
    • Multi-spectral image analysis
    • Illumination
    • Image segmentation
    • Image acquisition


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