Image processing issues in digital strain mapping

W. F. Clocksin, J. Quinta Da Fonseca, P. J. Withers, P. H S Torr

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    We have developed high density image processing techniques for finding the surface strain of an untreated sample of material from a sequence of images taken during the application of force from a test rig. Not all motion detection algorithms have suitable functional characteristics for this task, as image sequences are characterised by both short- and long-range displacements, non-rigid deformations, as well as a low signal-to-noise ratio and methodological artifacts. We show how a probability-based motion detection algorithm can be used as a high confidence estimator of the strain tensor characterising the deformation of the material. An important issue discussed is how to minimise the number of image brightness differences that need to be calculated. We give results from two studies of materials under axial tension: a sample of aluminium alloy exhibiting a propagating plastic deformation, and a preparation of deer antler bone, a natural composite material.
    Original languageEnglish
    Title of host publicationProceedings of SPIE - The International Society for Optical Engineering|Proc SPIE Int Soc Opt Eng
    EditorsA.G. Tescher
    Pages384-395
    Number of pages11
    Volume4790
    DOIs
    Publication statusPublished - 2002
    EventApplications of Digital Image Processing XXV - Seattle, WA
    Duration: 1 Jul 2002 → …

    Conference

    ConferenceApplications of Digital Image Processing XXV
    CitySeattle, WA
    Period1/07/02 → …

    Keywords

    • Image correlation
    • Image processing
    • Optical flow
    • Probabilistic
    • Strain mapping

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