Crossing points detection in plain weave for old paintings with deep learning

This is an open access article under the CC BY-NC-ND licenseIn the forensic studies of painting masterpieces, the analysis of the support is of major importance. For plain weave fabrics, the densities of vertical and horizontal threads are used as main features, while angle deviations from the vertical and horizontal axis are also of help. These features can be studied locally through the canvas. In this work, deep learning is proposed as a tool to perform these local densities and angle studies. We trained the model with samples from 36 paintings by Velázquez, Rubens or Ribera, among others. The data preparation and augmentation are dealt with at a first stage of the pipeline. We then focus on the supervised segmentation of crossing points between threads. The U-Net with inception and Dice loss are presented as good choices for this task. Densities and angles are then estimated based on the segmented crossing points. We report test results of the analysis of a few canvases and a comparison with methods in the frequency domain, widely used in this problem. We concluded that this new approach successes in some cases where the frequency analysis tools fail, while improves the results in others. Besides, our proposal does not need the labeling of part of the to be processed image. As case studies, we apply this novel algorithm to the analysis of two pairs of canvases by Velázquez and Murillo, to conclude that the fabrics used came from the same roll.Consejería de Transformación Económica, Industria, Conocimiento y Universidades, Junta de Andalucía y la Unión Europea P20_01216 PID2021-123182OB-I00 216 PID2021-127871OB-I00Ministerio de Ciencia e Innovación de España MCIN/AEI/10.13039/50110001103

Thread Counting in Plain Weave for Old Paintings Using Semi-Supervised Regression Deep Learning Models

In this work, the authors develop regression approaches based on deep learning to perform thread density estimation for plain weave canvas analysis. Previous approaches were based on Fourier analysis, which is quite robust for some scenarios but fails in some others, in machine learning tools, that involve pre-labeling of the painting at hand, or the segmentation of thread crossing points, that provides good estimations in all scenarios with no need of pre-labeling. The segmentation approach is time-consuming as the estimation of the densities is performed after locating the crossing points. In this novel proposal, we avoid this step by computing the density of threads directly from the image with a regression deep learning model. We also incorporate some improvements in the initial preprocessing of the input image with an impact on the final error. Several models are proposed and analyzed to retain the best one. Furthermore, we further reduce the density estimation error by introducing a semi-supervised approach. The performance of our novel algorithm is analyzed with works by Ribera, Vel\'azquez, and Poussin where we compare our results to the ones of previous approaches. Finally, the method is put into practice to support the change of authorship or a masterpiece at the Museo del Prado.Comment: 21 page

A literature review of analytical techniques for materials characterisation of painted textiles - Part 2: spectroscopic and chromatographic analytical instrumentation

Part Two of this Literature Review of analytical techniques for materials characterisation of painted textiles focusses on the application of vibrational and x-ray spectroscopic and chromatographic techniques used in the analysis of painted textiles to inform understanding of their materials, methods of making and degradation. The principles of detection methods, technique limitations and advantages, and how they complement each other, are explained and advances in techniques applicable in the study of painted textiles are discussed, such as mapping in Fourier transform infrared spectroscopy and Raman, surface-enhanced resonance Raman spectroscopy, and secondary ion mass spectrometry. Most informative work relating to painted textiles comes from close collaboration between conservators and scientists in interpreting findings and this literature review provides a useful starting point to further develop the capabilities of analytical techniques to enhance the study and conservation of painted textiles

Analytical investigation of the original painted canvas of Santa Irene, by Giuseppe Verrio (Church of Sant’Irene, Lecce, Italy)

The object of this study is unusual for both its material and technique. It is an oil painting on sheets of paper glued to a canvas made of linen fibres, thereby showing some execution peculiarities. It depicts the Virgin of Thessalonica in a hieratic attitude. The painting is attributed to the Salento-born artist Giuseppe Verrio (1639) for the church of the Theatine religious Order in Lecce, Italy, in which it is still placed, on the left altar of the transept. To truly understand and appreciate a work of art, it is important to have a basic knowledge of the materials and techniques used by the artist. For a better understanding of the execution techniques and to study the original materials and those that have been added over time, the painting was examined using the following analytical techniques: microscopic examination of cross-sections, μ-Raman spectroscopy and pyrolysis gas chromatography-mass spectrometry (Py-GC-MS). The data indicate that Verrio used different earthy, mineral and manufactured pigments, an organic dye used only on the paper, oil as a binder, and varnish as a protectant. The results demonstrate that the latter are both original and due to a subsequent restoration

Spectroscopy studies on conservation issues in modern and contemporary paintings

Dissertation presented to the Faculty of Sciences and Technology of New University of Lisbon in fulfilment of the requirements for the Master’s degree in Conservation and Restoration Specialization in easel paintingModern and contemporary paintings are one of today’s grand challenges in conservation of cultural heritage. Particularly, these paintings have often been retouched using materials rather similar to originals, thus, compromising the reversibility of the overpainting. In this work, FTIR and Raman spectroscopies, assisted by optical microscopy, were used to evaluate the effectiveness and harmfulness of chemical and laser cleaning methods for the removal of overpaints. Representative mock-ups prepared with commercial paint formulations were used. The laser cleaning experiment was part of an interdisciplinary study which aims the evaluation of method’s limitations by using the most aggressive cleaning parameters. The combined use of FTIR and Raman spectroscopies could identify constituent materials of modern paints, controlling their behaviour under cleaning, while optical microscopy allowed the evaluation on surface morphology. In addition, equivalent portable equipments from MOLAB were covered as a preparation for in situ analysis. Several problems in the selective removal of overpaints were found with chemical cleaning. The laser cleaning showed better efficiency in removing them, although, some alterations occurred upon laser irradiation, for instance, binder degradation with carbon formation and titanium white alteration. The proposed spectroscopic protocol was considered useful for controlling different cleaning methods in modern and contemporary paintings

Statistical Analysis in Art Conservation Research

Evaluates all components of data analysis and shows that statistical methods in conservation are vastly underutilized. Also offers specific examples of possible improvements

Multiscale approach in the assessment of nanocellulose-based materials as consolidants for painting canvases

This thesis investigates mainly the use of nanocellulose-based treatment for the consolidation of degraded cotton canvases of modern paintings and includes within this some case studies on linen canvases (sized and unsized) and 19th cent. historical samples from paintings. It. uses a multi-scale analytical approach where primarily controlled relative humidity dynamic mechanical analysis (DMA-RH) was used to evaluate the effect of the novel nanocellulose based preparations. It aims at quantifying the advantages, disadvantages, and limitations of their application. Initially, the baseline viscoelastic response to RH variations of a degraded cotton canvas was measured by DMA-RH. This technique was used further together with SEM to assess morphologically and mechanically 6 traditional consolidants including natural such as animal glue and synthetic materials. Following the same protocol, two solutions of nanocellulose-based consolidants developed in the frame of the Nanorestart project were assessed. These materials consisted of nanocellulose dispersions in water or water/ethanol and nanocomposites of nanocellulose-reinforced cellulose derivatives in polar/apolar solvents. Overall, higher consolidation at lower weight added was measured for the nanocellulose-based treatments tested when compared to the traditional consolidants. The penetration of the consolidant in the canvas also shows to greatly differ between treatments with the nanocellulose showing low penetration. Higher mechanical response to RH was also measured after treatment in particular with the water-based treatment. The results demonstrate how the adhesion, measured here at the nanoscale, and consolidant penetration into the canvas are dominant factors for the development of consolidation treatment for painting canvases. The assessment of the novel consolidants was finally carried out on historical canvases. Most treatments show to perform well on historical paintings in terms of handling properties, penetration and surface appearance and consolidation. Preliminary time-resolved neutron radiography with new purpose built sample chamber and RH controller provided visual information on time-dependent moisture response of the samples

Portrait of an artist at work: exploring Max Ernst's surrealist techniques

AbstractMax Ernst was one of the most influential artists associated with both the Dada and Surrealist movements. However, until now, only few scientific studies have been devoted to his works. This paper presents the results of a multi-analytical investigation on six oil paintings, made between 1927 and 1942, belonging to the Peggy Guggenheim Collection in Venice (Solomon R. Guggenheim Foundation, New York). Through a combined art historical and scientific approach, this study aims at understanding Ernst's painting techniques, including frottage, grattage, dripping, and decalcomania, the used materials, and the state of conservation of the artworks. Non-invasive in situ investigations were performed by means of Vis–NIR multi-spectral imaging, X-ray fluorescence, external reflection FTIR and Raman spectroscopy. Imaging analysis revealed important information about Ernst's painting methods while the other techniques provided useful information about the ground layer, the painting materials and the presence of alteration products. Ernst's palette discloses great freedom in his use of materials and evolution during the time. This investigation demonstrates that an integrated, non-invasive, diagnostic approach provides a thorough analysis of materials and execution techniques of Ernst' masterworks allowing an in-depth knowledge of his highly skilled work