Improvement of the digital radiographic images of old paintings on wooden support through the anisotropic diffusion method

Autor: Amir Movafeghi, Effat Yahaghi, José Antonio Madrid García
Rok vydání: 2021
Předmět:
Zdroj: RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
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ISSN: 1296-2074
DOI: 10.1016/j.culher.2021.02.008
Popis: The main defect types of historic-artistic paintings on wood are ruptures, scratches, twisting and such which may be inflicted by environment conditions, insects, dust, and dirt as well as by physical damage. The exact localization of the defects and determination of their extent may be achieved using industrial radiography as a non-destructive testing method. The radiographs thus produced may suffer from blurriness mainly due to the inherent scattering of X-rays especially in the case of paintings on a wooden base and hindering therefore accurate detection of the size and shape of such defects. Image processing methods have been employed to reduce the blurriness of images leading to improved analysis of the images. In this study, an image processing method based on anisotropic diffusion with an automatic threshold level was applied to achieve improved outcomes. The reconstructed images of the implemented algorithm yielded sharper edges. Defects such as those due to xylophagous attack, the effect of the brushstrokes, superficial fissures, oxidation of the nails, and the different types of construction woods were better visualized than from the original image. The algorithm was shown to be useful by operators including painting conservators for their procedures.
Databáze: OpenAIRE
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