This article discusses a number of modern techniques used for the analysis of works of art. The most widely used approaches as well as lesser known ones are outlined in terms of their applications and the kind of information on the condition of artworks that can be extracted. Special attention is paid to the method of thermographic analysis of works of pictorial art. The principles of the technique, various computational approaches, and safety concerns are discussed. A set of examples is provided for the demonstration of the capabilities of thermographic assessment, including a range of real canvas and panel paintings exhibited in museums and in private collections. PACS Nos.: 87.63.Hg, 78.20.nb, 81.70.Pg, 07.20.-n. Résumé : Nous discutons ici de techniques modernes utilisées pour analyser les oeuvres d'art. Nous présentons les méthodes les plus connues comme les moins connues, selon leurs applications et la sorte d'information qu'on peut extraire sur les conditions de l'oeuvre d'art. Nous portons une attention spéciale à l'analyse thermographique d'oeuvres picturales. Nous discutons les principes de la technique, des différentes approches informatiques et des soucis de sécurité. Nous présentons un ensemble d'exemples pour illustrer les capacités de l'évaluation thermographique, incluant plusieurs véritables tableaux et panneaux peints exposés dans des musées et des collections privées. [Traduit par la Rédaction]

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Thermography is a powerful tool for non-destructive testing of a wide range of materials. Thermography has a number of approaches differing in both experiment setup and the way the collected data are processed. Among such approaches is the Principal Component Thermography (PCT) method, which is based on the statistical processing of raw thermal images collected by thermal camera. The processed images (principal components or empirical orthogonal functions) form an orthonormal basis, and often look like a superposition of all possible structural features found in the object under inspection-i.e., surface heating non-uniformity, internal defects and material structure. At the same time, from practical point of view it is desirable to have images representing independent structural features. The work presented in this paper proposes an approach for separation of independent image patterns (archetypes) from a set of principal component images. The approach is demonstrated in the application of inspection of composite materials as well as the non-invasive analysis of works of art.

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