Oil painting teaching design based on the mobile platform in higher art education.

To improve the current oil painting teaching mode in Chinese universities, this study combines deep learning technology and artificial intelligence technology to explore oil painting teaching. Firstly, the research status of individualized education and related research on image classification based on brush features are analyzed. Secondly, based on a convolutional neural network, mathematical morphology, and support vector machine, the oil painting classification model is constructed, in which the extracted features include color and brush features. Moreover, based on artificial intelligence technology and individualized education theory, a personalized intelligent oil painting teaching framework is built. Finally, the performance of the intelligent oil painting classification model is evaluated, and the content of the personalized intelligent oil painting teaching framework is explained. The results show that the average classification accuracy of oil painting is 90.25% when only brush features are extracted. When only color features are extracted, the average classification accuracy is over 89%. When the two features are extracted, the average accuracy of the oil painting classification model reaches 94.03%. Iterative Dichotomiser3, decision tree C4.5, and support vector machines have an average classification accuracy of 82.24%, 83.57%, and 94.03%. The training speed of epochs data with size 50 is faster than that of epochs original data with size 100, but the accuracy is slightly decreased. The personalized oil painting teaching system helps students adjust their learning plans according to their conditions, avoid learning repetitive content, and ultimately improve students' learning efficiency. Compared with other studies, this study obtains a good oil painting classification model and a personalized oil painting education system that plays a positive role in oil painting teaching. This study has laid the foundation for the development of higher art education.

Microbial communities adhering to the obverse and reverse sides of an oil painting on canvas: identification and evaluation of their biodegradative potential.

In this study, we investigated and compared the microbial communities adhering to the obverse and the reverse sides of an oil painting on canvas exhibiting signs of biodeterioration. Samples showing no visible damage were investigated as controls. Air samples were also analysed, in order to investigate the presence of airborne microorganisms suspended in the indoor atmosphere. The diversity of the cultivable microorganisms adhering to the surface was analysed by molecular techniques, such as RAPD analysis and gene sequencing. DGGE fingerprints derived from DNA directly extracted from canvas material in combination with clone libraries and sequencing were used to evaluate the non-cultivable fraction of the microbial communities associated with the material. By using culture-dependent methods, most of the bacterial strains were found to be common airborne, spore-forming microorganisms and belonged to the phyla Actinobacteria and Firmicutes, whereas culture-independent techniques identified sequenced clones affiliated with members of the phyla Actinobacteria and Proteobacteria. The diversity of fungi was shown to be much lower than that observed for bacteria, and only species of Penicillium spp. could be detected by cultivation techniques. The selected strategy revealed a higher microbial diversity on the obverse than on the reverse side of the painting and the near absence of actively growing microorganisms on areas showing no visible damage. Furthermore, enzymatic activity tests revealed that the most widespread activities involved in biodeterioration were esterase and esterase lipase among the isolated bacterial strains, and esterase and N-acetyl-ß-glucosaminidase among fungi strains.

Combined Use of Non-Invasive and Micro-Invasive Analytical Investigations to Understand the State of Conservation and the Causes of Degradation of I Tesori del Mare (1901) by Plinio Nomellini.

In this study, the investigation of the oil painting on canvas I Tesori del Mare made by Plinio Nomellini in 1901 is presented. The aim of the research was threefold: the examination of the state of conservation in view of the restoration treatment, together with the identification of the causes of degradation and the study of the artistic technique. During the years, the artwork underwent several cleaning and fixing interventions, resulting in a patchy appearance of the surface. Nevertheless, the presence of consistent liftings persists, while the protective coating shows uneven chromatic alteration, both requiring further analysis. Multispectral imaging allowed for better visualization of the figuration's structure and the restored areas. The combined use of Raman spectroscopy, Fourier Transform Infrared spectroscopy in the Attenuated Total Reflection mode (FT-IR ATR), and Scanning Electron Microscopy coupled with an Energy Dispersive Spectroscopy (SEM/EDS) enabled better understanding of the stratigraphy through the identification of some pigments, the binder, and the aged varnish layer on the top. SEM/EDS highlighted the presence of zinc in both the ground layer and the paint layers. Furthermore, FT-IR ATR spectroscopy showed peaks related to metal soaps such as zinc stearate, which are known to cause severe delamination of the paint layers, explaining the recurring lifting issues. Eventually, the varnish layer was found to be acrylic resin, presumably mixed with varnishes applied in past restoration treatments.

A Novel Multi-Feature Fusion Method in Merging Information of Heterogenous-View Data for Oil Painting Image Feature Extraction and Recognition.

The art of oil painting reflects on society in the form of vision, while technology constantly explores and provides powerful possibilities to transform the society, which also includes the revolution in the way of art creation and even the way of thinking. The progress of science and technology often provides great changes for the creation of art, and also often changes people's way of appreciation and ideas. The oil painting image feature extraction and recognition is an important field in computer vision, which is widely used in video surveillance, human-computer interaction, sign language recognition and medical, health care. In the past few decades, feature extraction and recognition have focused on the multi-feature fusion method. However, the captured oil painting image is sensitive to light changes and background noise, which limits the robustness of feature extraction and recognition. Oil painting feature extraction is the basis of feature classification. Feature classification based on a single feature is easily affected by the inaccurate detection accuracy of the object area, object angle, scale change, noise interference and other factors, resulting in the reduction of classification accuracy. Therefore, we propose a novel multi-feature fusion method in merging information of heterogenous-view data for oil painting image feature extraction and recognition in this paper. It fuses the width-to-height ratio feature, rotation invariant uniform local binary mode feature and SIFT feature. Meanwhile, we adopt a modified faster RCNN to extract the semantic feature of oil painting. Then the feature is classified based on the support vector machine and K-nearest neighbor method. The experiment results show that the feature extraction method based on multi-feature fusion can significantly improve the average classification accuracy of oil painting and have high recognition efficiency.

3D Printing of Oil Paintings Based on Material Jetting and Its Reduction of Staircase Effect.

Material jetting is a high-precision and fast 3D printing technique for color 3D objects reproduction, but it also suffers from color accuracy and jagged issues. The UV inks jetting processes based on the polymer jetting principle have been studied from printing materials regarding the parameters in the default layer order, which is prone to staircase effects. In this work, utilizing the Mimaki UV inks jetting system with a variable layer thickness, a new framework to print a photogrammetry-based oil painting 3D model has been proposed with the tunable coloring layer sequence to improve the jagged challenge between adjacent layers. Based on contour tracking, a height-rendering image of the oil painting model is generated, which is further segmented and pasted to the corresponding slicing layers to control the overall printing sequence of coloring layers and white layers. The final results show that photogrammetric models of oil paintings can be printed vividly by UV-curable color polymers, and that the proposed reverse-sequence printing method can significantly improve the staircase effect based on visual assessment and color difference. Finally, the case of polymer-based oil painting 3D printing provides new insights for optimizing color 3D printing processes based on other substrates and print accuracy to improve the corresponding staircase effect.

Natural products such as adhesives in oil paintings.

The study and analysis of the materials employed in artistic paintings provide deeper knowledge about the history of the work of art, including restoration efforts made in the past, and the development of painting techniques through the centuries. Gas chromatography coupled to mass spectrometry is the main analytical technique employed, as it proved to be the most suitable technique for the analysis of complex mixtures, thanks to its combination of sensitivity, wide range of applicability and versatility. Further, µFT-IR technique has also been employed to get a preliminary screening of the samples taken from paintings. In this paper, the analytical protocol based on these two techniques has been applied for analysing natural terpenic resins; its performance has been tested on microsamples collected from paintings of valuable artistic interest.

Fourier Transform Infrared (FT-IR) Microspectroscopy of 20th Century Russian Oil Paintings: Problem of Dating.

Analysis of the IR spectra of samples from 230 Russian oil paintings of the 20th century is used to propose a procedure for the threshold estimation of the age of paintings based on measured parameters (intensity ratios of spectral bands). The bands of compounds that are formed upon interaction of pigment (zinc white) with oil are used for dating.

An analytical Raman spectroscopic study of an important english oil painting of the 18th Century.

An opportunity was afforded to analyse pigment specimens from an unrestored oil painting in the style of the English School of the mid-18th Century prior to conservation being undertaken. Raman spectroscopy was adopted to characterise the pigments and indicated the presence of a novel red pigment which was assigned to the complex chromium mineral, hemihedrite, in addition to other interesting materials found in combination. This is the first recorded identification of hemihedrite spectral signals in an art context in a range of mineral pigments that are otherwise typical of this period and some hypotheses are presented to explain its presence based on its occurrence with associated mineral pigments. It is suggested that the presence of powdered glass identified in certain areas of the painting enhanced the reflectivity of the pigment matrix.

Difference in brain activations during appreciating paintings and photographic analogs.

Several studies have investigated neural correlates of aesthetic appreciation for paintings but to date the findings have been heterogeneous. This heterogeneity may be attributed to previous studies' measurement of aesthetic appreciation of not only the beauty of paintings but also the beauty of motifs of the paintings. In order to better elucidate the beauty of paintings, it seems necessary to compare aesthetic appreciation of paintings and photographic analogs which included corresponding real images. We prepared for famous painters' pictures and their photographic analogs which were set up to resemble each painting in order to investigate the hypothesis that there exist specific neural correlates associated with the aesthetic appreciation for paintings. Forty-four subjects participated in functional magnetic resonance study which required comparisons of aesthetic appreciation of paintings of still life and landscape versus photographic analogs including corresponding real images of still life and landscape. Bilateral cuneus and the left lingual gyrus were activated in the comparison of aesthetic appreciation of paintings versus photographic analogs. In conclusion, the present findings suggest a possibility of the existence of specific neural correlates associated with the aesthetic appreciation for paintings and that bilateral cuneus and the left lingual gyrus may be involved.