Infrared thermography (IRT) technology has evolved during the last decade extending its capabilities to the industrial and infrastructures level. Because of the necessity to perform regular inspections of in-service assets such as bridges, it becomes necessary to investigate and develop efficient inspection technologies that can adapt to the needs of the industry. So, IRT is considered an effective technology to perform NDE. However, its integration with other sensing technologies such as visible cameras still needs to be further investigated so the inspection and maintenance strategy can be more effective when inspecting large structures and assets. Hence, this project investigates fusion strategies and proposes a multi-modal processing pipeline using a deep learning-based panorama stitching method for infrared and visible images. Then, an image registration method to fuse infrared and visible images so identification of defects in visible and thermal spectra becomes more efficient.


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    Titel :

    Multi-modal image processing pipeline for NDE of structures and industrial assets


    Beteiligte:
    Avdelidis, Nicolas P. (Herausgeber:in) / Shahsavarani, S. (Autor:in) / Lopez, Fernando (Autor:in) / Maldague, Xavier (Autor:in)

    Kongress:

    Thermosense: Thermal Infrared Applications XLV ; 2023 ; Orlando, Florida, United States


    Erschienen in:

    Proc. SPIE ; 12536


    Erscheinungsdatum :

    2023-06-12





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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