Fracture and internal structure detection of ceramic objects using improved digital radiography images.

• Radiography testing (RT) is an effective, non-invasive method for the detection of hidden structures and details of ancient ceramic objects. • The image processing methods are the efficient tool for maximizing of detail extraction from the radiographs. • The fast bilateral filter (FBF) is a fast i...

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Publicado en:Journal of Cultural Heritage Vol. 44; pp. 152 - 163
Autores principales: Yahaghi, Effat, Madrid Garcia, Jose A., Movafeghi, Amir
Formato: Artículo
Publicado: Elsevier B.V. Jul2020
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      jtl: Journal of Cultural Heritage
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      dt: Jul2020
      vid: 44
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      pub: Elsevier B.V.
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        145035063
        10.1016/j.culher.2020.02.003
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        atl: Fracture and internal structure detection of ceramic objects using improved digital radiography images.
      aug:
        au:
          Yahaghi, Effat
          Madrid Garcia, Jose A.
          Movafeghi, Amir
        affil:
          Imam Khomeini International University, Qazvin, Iran
          University Institute for the Restoration of the Patrimony, Universitat Politècnica de València, Valencia, Spain
          Nuclear Science and Technology Research Institute (NSTRI), Tehran, Iran
      su:
        Digital images
        Medical digital radiography
        Image processing
        Manufacturing processes
        Gaussian function
        Data modeling
        Spain
      sug:
        subj:
          Spain
          Digital images
          Medical digital radiography
          Image processing
          Manufacturing processes
          Gaussian function
          Data modeling
      keyword:
        Ceramic antique object
        Fast bilateral filter
        Fracture detection
        Internal structure
        Radiography testing
      ab: • Radiography testing (RT) is an effective, non-invasive method for the detection of hidden structures and details of ancient ceramic objects. • The image processing methods are the efficient tool for maximizing of detail extraction from the radiographs. • The fast bilateral filter (FBF) is a fast image processing method that enhances visualization of the radiographs of ceramic objects. • Thanks to the FBF; the pathologies of the objects and the hidden morphologies of art pieces can be dimensioned much better in enhanced image. • Better visualization of the processed radiographs have been confirmed by the conservators and restaurateurs of cultural heritage. Radiography testing (RT) is an effective, non-invasive method for the detection of hidden structures, details and fracture regions of valuable ancient ceramic objects. To maximize detail extraction from the radiographs and to better interpret images, we use an efficient image processing method that reveals the design and defect regions of objects. For larger radiographic images, it is preferable that a desktop computer is capable of processing the algorithm. Algorithms that require a large memory size and CPU time necessitate the resizing of the images, resulting in lower quality output images. In this study, the fast bilateral filter (FBF) was implemented to enhance the visualization of the radiographs of ceramic objects from the archaeological museum of Burriana, Spain. The digital radiographs were provided by a computed radiography (CR) system at the Laboratory of Documentation and Registration in the University Institute for the Restoration of the Patrimony (IRP) of the Universitat Politècnica de València (UPV), Spain. The FBF method based on the Fourier series and the truncated Gaussian function was successfully implemented with radiographs of antique objects. The results show that the internal structures, manufacturing processes, and fractures are better visualized and the edges and fine details are preserved. The design details were shown to be better visualized than the original radiographs based on opinions and evaluations from experts in radiography and the conservation and restoration of cultural heritage.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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