Detecting Defects in Mural Paintings: An Innovative Approach Based on Thermal Correlation and 3D Micro-Morphological Mapping

Uncovering hidden subsurface features in mural paintings represents a fundamental chal lenge in cultural heritage conservation. Given the complex stratigraphy of these artworks, deterioration phenomena occur at various depths, making the non-destructive detection of internal defects essential for accurate condition assessment. This study presents an in novative approach designed to characterize mortar substrates by integrating active ther mography with high-resolution optical microprofilometry. To validate this methodology, a set of controlled mortar samples exhibiting different surface morphologies and internal defects and a real mural painting were analysed. Thermographic surveys were conducted in both the Mid-Wave and Long-Wave infrared spectral bands, while surface topography was acquired using a custom-developed optical profilometer. This integrated approach enabled the correlation of thermographic signals with surface morphological features. To accurately map subsurface defects characterized by distinct thermal signatures, a novel method, based on thermal correlation analysis and named Thermal Correlation Mapper (TCM), was developed. The algorithm was evaluated through comparison with other sim ilarity measures, including deterministic and stochastic methods, and validated on both laboratory mock-ups and real-world case studies. The results demonstrate that this com bined workflow effectively isolates internal defects. This work constitutes the first appli cation of the TCM algorithm, thereby providing a new tool for the diagnostic imaging of historic wall paintings.