Reliability increase of masonry characteristics estimation by a sampling algorithm applied to thermographic digital images

In this paper the estimation of masonry characteristics by means of thermographic images, enhanced by sampling Kantorovich algorithm, is taken into account. In particular, the convergence of the Statistical Volume Element (SVE) to the Representative Volume Element (RVE) is analyzed. It is found that the enhancement, obtained by the proposed procedure, allows a faster convergence of SVE to RVE and a reduced coefficient of variation of the estimates obtained using a partition of the image with windows of smaller dimensions. Moreover, the effects of the uncertainties in the parameters involved in the reconstruction of texture from thermographic image, such as those used in morphological operators employed in digital image processing, involving the environmental conditions of the samples and the properties of the kernel utilized in the image enhancement algorithm, have been studied in order to assess their influence on the estimated mechanical characteristics. The performed analyses contribute to increase the reliability of the thermography as tool for identifying of masonries covered with plaster or frescoes, which is a very frequent case in vulnerability analysis of historical buildings.