Evaluating quality of marquetries by applying active IR thermography and advanced signal processing

Marquetry method is important in the culture of the Italian community as can be witnessed from the large quantity of artworks that have been realized in this way. The monitoring of the integrity of such pieces poses a great challenge given the need for a reliable and nondestructive technique able to detect surface and subsurface defects. In this work, two ancient marquetry samples containing natural defects were inspected thanks to active thermography by using time-tested, safe, and resilient advanced signal processing algorithms (i.e., principal component thermography, correlation contrast, pulsed phase Fourier transform amplitude and phase, cold image subtraction contrast, and polynomial fitting). The latter have been applied to provide a 2D map of the defects. Anyway, in the cultural heritage field, one of the main interests of restorers is the volume of the subsurface defects for structural analyses. The emphasis in this study is placed on the use of dynamic thermal tomography (DTT) as an advanced technique of active thermal nondestructive testing. The main concepts of DTT are illustrated in the manuscript, while a special technique for defect thermal characterization has been used during the second analysis to validate tomographic results. Finally, the position of the main defects retrieved by means of the established techniques applied during the first analysis has been confirmed by DTT.

Automated summary

Marquetry method plays a significant role in Italian culture, as evidenced by the large number of artworks created in this way. Active thermography, along with advanced signal processing algorithms, was used to inspect marquetry samples with natural defects, while dynamic thermal tomography was employed as an advanced technique for nondestructive testing and defect quantification. The use of established techniques combined with DTT proved successful in identifying and confirming the positions of main defects in the samples.