A New Quantitative Method for the Non-Invasive Documentation of Morphological Damage in Paintings Using RTI Surface Normals

Sensors

Marcello Manfredi⁴  Greg Bearman⁵  Greg Williamson²  Dale Kronkright¹  Eric Doehne³  Megan Jacobs² 

[1] Georgia O'Keeffe Museum, Santa Fe, NM 87501, USA; E-Mail:;Media Arts Faculty, New Mexico Highland University, Las Vegas, NM 87701, USA; E-Mails:;Conservation Sciences, Pasadena, CA 91104, USA; E-Mail:;Department of Sciences and Technological Innovation, University of Easter Piedmont, Viale T. Michel 11, Alessandria 15121, Italy; E-Mail:;ANE Image, Pasadena, CA 91104, USA; E-Mail:

关键词: damage detection;    reflectance transformation imaging;    monitoring conservation;    cultural heritage;    3D surface;    change over time;   

DOI  :  10.3390/s140712271

来源: mdpi

【 摘 要 】

In this paper we propose a reliable surface imaging method for the non-invasive detection of morphological changes in paintings. Usually, the evaluation and quantification of changes and defects results mostly from an optical and subjective assessment, through the comparison of the previous and subsequent state of conservation and by means of condition reports. Using quantitative Reflectance Transformation Imaging (RTI) we obtain detailed information on the geometry and morphology of the painting surface with a fast, precise and non-invasive method. Accurate and quantitative measurements of deterioration were acquired after the painting experienced artificial damage. Morphological changes were documented using normal vector images while the intensity map succeeded in highlighting, quantifying and describing the physical changes. We estimate that the technique can detect a morphological damage slightly smaller than 0.3 mm, which would be difficult to detect with the eye, considering the painting size. This non-invasive tool could be very useful, for example, to examine paintings and artwork before they travel on loan or during a restoration. The method lends itself to automated analysis of large images and datasets. Quantitative RTI thus eases the transition of extending human vision into the realm of measuring change over time.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.