Fourier interpolation and neural network analysis for accurate 3D reconstruction of images produced by an inductive sensor

Muhammad Zaid, Patrick Gaydecki, Sung Quek, Graham Miller, Bosco Fernandes

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

    Abstract

    This paper describes a novel methodology to reduce the scanning time and to extract bar dimensional information from images generated by an inductive sensor. Using a sparsely populated data set obtained from a reduced number of scan lines, faster high resolution images are generated using image interpolation techniques. Having generated these images, image filtering, peak picking and neural networks methods are applied to extract bar dimensional information and accurate 3 D visualization.

    Original languageEnglish
    Title of host publicationReview of Progress in Quantitative Nondestructive Evaluation Volume 24
    Pages836-843
    Number of pages8
    Volume760
    DOIs
    Publication statusPublished - 9 Apr 2005
    EventReview of Progress in Quantitative Nondestructive Evaluation - Golden, CO, United States
    Duration: 25 Jul 200430 Jul 2004

    Conference

    ConferenceReview of Progress in Quantitative Nondestructive Evaluation
    Country/TerritoryUnited States
    CityGolden, CO
    Period25/07/0430/07/04

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