Neural Networks for Hyperspectral Imaging of Historical Paintings: A Practical Review

Hyperspectral imaging (HSI) has become widely used in cultural heritage (CH). This very efficient method for artwork analysis is connected with the generation of large amounts of spectral data. The effective processing of such heavy spectral datasets remains an active research area. Along with the firmly established statistical and multivariate analysis methods, neural networks (NNs) represent a promising alternative in the field of CH. Over the last five years, the application of NNs for pigment identification and classification based on HSI datasets has drastically expanded due to the flexibility of the types of data they can process, and their superior ability to extract structures contained in the raw spectral data. This review provides an exhaustive analysis of the literature related to NNs applied for HSI data in the CH field. We outline the existing data processing workflows and propose a comprehensive comparison of the applications and limitations of the various input dataset preparation methods and NN architectures. By leveraging NN strategies in CH, the paper contributes to a wider and more systematic application of this novel data analysis method

The ThomX project status

Work supported by the French Agence Nationale de la recherche as part of the program EQUIPEX under reference ANR-10-EQPX-51, the Ile de France region, CNRS-IN2P3 and Université Paris Sud XI - http://accelconf.web.cern.ch/AccelConf/IPAC2014/papers/wepro052.pdfA collaboration of seven research institutes and an industry has been set up for the ThomX project, a compact Compton Backscattering Source (CBS) based in Orsay - France. After a period of study and definition of the machine performance, a full description of all the systems has been provided. The infrastructure work has been started and the main systems are in the call for tender phase. In this paper we will illustrate the definitive machine parameters and components characteristics. We will also update the results of the different technical and experimental activities on optical resonators, RF power supplies and on the electron gun

Rheology of white paints: How Van Gogh achieved his famous impasto

International audiencePaints based on white pigments are the basic materials found in ground layers of ready-made canvases as well as in painting layers mixed with other colours. It is surprising that Vincent Van Gogh, whose unique style is world famous, resorted to not one but two types of white paints. Indeed, Van Gogh often used both lead white and zinc white in the very same painting, contrasting then with the majority of his contemporaries who have only used the traditional lead white. To trace the evolution of his painting technique and to respond to the issues of authentication, dating and preservation raised by his artwork, it is essential to have a good knowledge of the painting materials he used and how he used them.This paper describes the reconstructions of 19th century white paint formulations and their rheological characterization in order to compare their flow properties: by adjusting them, different paint finishes from smooth surfaces to high impastos can be produced. We define a general procedure for paint rheology characterization, useful for old recipes reconstructions in the field of conservation science. Both lead white and zinc white based paints exhibit a similar rheological behaviour, with a fluid to solid transition, and variations of their properties such as yield stress and elastic moduli, depending on their formulation (oil nature, content, and treatment). An explanation on the specific use of zinc white can be proposed as it allows higher impastos than a lead white paint containing the same oil content