Bibliography

(eng): Our paper introduces a system based on digital image processing algorithms designed to facilitate analysis of painting materials during artwork conservation. Microscopic images of minute samples - cross sections – from the artworks are scanned using visible and ultraviolet spectra and under scanning electron microscope. Firstly, the scans are registered to remove geometrical differences. The multimodal nature of the problem led to the application of mutual information. The image quality is maximized by means of blind deconvolution methods. Cross-sections are then segmented to individual layers and distinctive seeds. For the image retrieval part, which facilitates further analyzes and conclusions, the layers are represented by means of wavelet analysis and secondorder statistics. The library of such features can be connected to the time of creation and differences between vectors of the same materials but from different paintings can help during a painter authentication.