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Ultrasonic imaging of standing trees: factors influencing the decay detection

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  • Additional Information
    • Contributors:
      Universidad Nacional de Colombia Bogotà (UNAL); Universidad Nacional de Colombia Sede Manizales; Universidad Nacional de Colombia; BioWooEB (UPR BioWooEB); Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM); Ondes et Imagerie (O&I); Laboratoire de Mécanique et d'Acoustique Marseille (LMA ); Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS)
    • Publication Information:
      HAL CCSD
    • Publication Date:
      2019
    • Collection:
      Aix-Marseille Université: HAL
    • Subject Terms:
    • Abstract:
      International audience ; Ultrasound Computed Tomography is a widely used technique for nondestructive control of materials. One application is the evaluation of the inner state of standing trees in urban areas. The quality of the tomographic image depends on several factors, such as the number of probes used and the image reconstruction algorithm. Here we are interested in evaluating the influence of using a reconstruction algorithm adapted to wood anisotropy, compared to the classic methods using an isotropic model, and the effect of numerically increasing the number of sensors and the time-of-flight measurements using an interpolation method, known as sinogram interpolation. A numerical configuration was tested, simulating the presence of an eccentric defect in a wood section. Reconstructed images were compared before and after the interpolation process, and a thresholding was applied to quantify the decay area estimation. A more detailed defect identification was obtained with the reconstruction algorithm adapted to wood anisotropy and the interpolation of the sensors.
    • Relation:
      hal-02290112; https://hal.science/hal-02290112; https://hal.science/hal-02290112/document; https://hal.science/hal-02290112/file/C4_STSIVA2019_Article.pdf
    • Accession Number:
      10.1109/STSIVA.2019.8730215
    • Online Access:
      https://doi.org/10.1109/STSIVA.2019.8730215
      https://hal.science/hal-02290112
      https://hal.science/hal-02290112/document
      https://hal.science/hal-02290112/file/C4_STSIVA2019_Article.pdf
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • Accession Number:
      edsbas.39BD8DAE