Craquelure as a Graph: Application of Image Processing and Graph Neural Networks to the Description of Fracture Patterns

Cracks on a painting is not a defect but an inimitable signature of an artwork which can be used for origin examination, aging monitoring, damage identification, and even forgery detection. This work presents the development of a new methodology and corresponding toolbox for the extraction and characterization of information from an image of a craquelure pattern. The proposed approach processes craquelure network as a graph. The graph representation captures the network structure via mutual organization of junctions and fractures. Furthermore, it is invariant to any geometrical distortions. At the same time, our tool extracts the properties of each node and edge individually, which allows to characterize the pattern statistically. We illustrate benefits from the graph representation and statistical features individually using novel Graph Neural Network and hand-crafted descriptors correspondingly. However, we also show that the best performance is achieved when both techniques are merged into one framework. We perform experiments on the dataset for paintings' origin classification and demonstrate that our approach outperforms existing techniques by a large margin.Comment: Published in ICCV 2019 Workshop

Virtual restoration of the Ghent altarpiece using crack detection and inpainting

In this paper, we present a new method for virtual restoration of digitized paintings, with the special focus on the Ghent Altarpiece (1432), one of Belgium's greatest masterpieces. The goal of the work is to remove cracks from the digitized painting thereby approximating how the painting looked like before ageing for nearly 600 years and aiding art historical and palaeographical analysis. For crack detection, we employ a multiscale morphological approach, which can cope with greatly varying thickness of the cracks as well as with their varying intensities (from dark to the light ones). Due to the content of the painting (with extremely many fine details) and complex type of cracks (including inconsistent whitish clouds around them), the available inpainting methods do not provide satisfactory results on many parts of the painting. We show that patch-based methods outperform pixel-based ones, but leaving still much room for improvements in this application. We propose a new method for candidate patch selection, which can be combined with different patch-based inpainting methods to improve their performance in crack removal. The results demonstrate improved performance, with less artefacts and better preserved fine details

Color segmentation and neural networks for automatic graphic relief of the state of conservation of artworks

none5noThis paper proposes a semi-automated methodology based on a sequence of analysis processes performed on multispectral images of artworks and aimed at the extraction of vector maps regarding their state of conservation. The graphic relief of the artwork represents the main instrument of communication and synthesis of information and data acquired on cultural heritage during restoration. Despite the widespread use of informatics tools, currently, these operations are still extremely subjective and require high execution times and costs. In some cases, manual execution is particularly complicated and almost impossible to carry out. The methodology proposed here allows supervised, partial automation of these procedures avoids approximations and drastically reduces the work times, as it makes a vector drawing by extracting the areas directly from the raster images. We propose a procedure for color segmentation based on principal/independent component analysis (PCA/ICA) and SOM neural networks and, as a case study, present the results obtained on a set of multispectral reproductions of a painting on canvas.openAnnamaria Amura, Anna Tonazzini, Emanuele Salerno, Stefano Pagnotta, Vincenzo PalleschiAmura, Annamaria; Tonazzini, Anna; Salerno, Emanuele; Pagnotta, Stefano; Palleschi, Vincenz

Image and Video Processing for Cultural Heritage

Charvillat V., Tonazzini A., Van Gool L., Nikolaidis N., ''Editorial: Image and video processing for cultural heritage'', EURASIP journal on image and video processing, vol. 2009, Article ID 163064, 3 pp., 2010.status: publishe

Digital image processing of the Ghent altarpiece : supporting the painting's study and conservation treatment

In this article, we show progress in certain image processing techniques that can support the physical restoration of the painting, its art-historical analysis, or both. We show how analysis of the crack patterns could indicate possible areas of overpaint, which may be of great value for the physical restoration campaign, after further validation. Next, we explore how digital image inpainting can serve as a simulation for the restoration of paint losses. Finally, we explore how the statistical analysis of the relatively simple and frequently recurring objects (such as pearls in this masterpiece) may characterize the consistency of the painter’s style and thereby aid both art-historical interpretation and physical restoration campaign

Sampled 3D models for Cultural Heritage: which uses beyond visualization?

[EN] Digital technologies are now mature for producing high quality digital replicas of Cultural Heritage (CH) artefacts. The research results produced in the last decade have shown an impressive evolution and consolidation of the technologies for acquiring high-quality digital 3D models (3D scanning) and for rendering those models at interactive speed. Technology is now mature enough to push us to go beyond the plain visualization of those assets, devising new tools able to extend our insight and intervention capabilities and to revise the current consolidated procedures for CH research and management. The paper presents a few recent experiences where high-quality 3D models have been used in CH research, restoration and conservation. These examples constitutes a broad review of different uses of digital 3Dassets in the CH domain.[ES] Se puede afirmar que las tecnologías digitales han alcanzado un punto de madurez suficiente como para producir réplicas digitales de alta calidad del patrimonio cultural, especialmente de artefactos. Los resultados de la investigación producidos en la última década han mostrado una impresionante evolución y consolidación de las tecnologías utilizadas para la producción de modelos digitales 3D de alta calidad (escaneado 3D) y para el renderizado de esos modelos a una velocidad interactiva. En este sentido la tecnología es hoy perfectamente capaz de empujarnos a ir más allá de la simple visualización de los bienes culturales, hasta elaborar nuevas herramientas capaces de ampliar nuestra visión y capacidades de intervención así como de revisar los procedimientos actuales de investigación y gestión del patrimonio cultural. Este artículo presenta algunas experiencias recientes en las que modelos 3D de alta calidad han sido utilizados para mejorar la investigación, restauración y conservacióThe research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007- 2013) under grant agreements no. 231809 (IST IP "3DCOFORM") and no. 270404 (IST NoE "V-Must.Net").Scopigno, R. (2012). Sampled 3D models for Cultural Heritage: which uses beyond visualization?. Virtual Archaeology Review. 3(5):109-115. https://doi.org/10.4995/var.2012.4537OJS10911535CALLIERI M., CIGNONI P., GANOVELLI F., IMPOCO G., MONTANI C., PINGI P., PONCHIO F., SCOPIGNO R. (2004): "Visualization and 3D data processing in David's restoration". IEEE Computer Graphics & Applications 24, 2 (Mar.-Apr. 2004), pp. 16-21. http://dx.doi.org/10.1109/MCG.2004.1274056CORSINI M., DELLEPIANE M., DERCKS U., PONCHIO F., CALLIERI M., KEULTJES D., MARINELLO A., SIGISMONDI R., SCOPIGNO R., WOLF G. (2010): "Cenobium - putting together the romanesque cloister capitals of the mediterranean region". In Bar International Series BAR S2118 2010 (Proc. of III International Conference on Remote Sensing in Archaeology, 17th-21st August 2009) (2010), S. Campana M. F., Liuzza C., (Eds.), pp. 189-194.DELLEPIANE M., CALIERI M., DELL'UNTO N. (2011): "Monitoring archeological excavation using dense stereo matching techniques". Tech. rep., CNR-ISTI, Pisa, Italy, 2011.DELLEPIANE M., CALLIERI M., FONDERSMITH M., CIGNONI P., SCOPIGNO R. (2007): "Using 3D scanning to analyze a proposal for the attribution of a bronze horse to Leonardo da Vinci". In The 8th Int. Symp. on International Symposium on Virtual Reality, Archaeology and Cultural Heritage (VAST 07) (Nov 2007), Eurographics, pp. 117-124.DYLLA K., FRISCHER B., MUELLER P., ULMER A., HAEGLER S. (2009): "Rome Reborn 2.0: A case study of virtual city reconstruction using procedural modeling techniques". In 37th Proceedings of the CAA Conference, March 22-26, 2009 (2009), pp. 62-66.HUANG Q.-X., FLORY S., GELFAND N., HOFER M., POTTMANN H. (2006): "Reassembling fractured objects by geometric matching". ACM Trans. Graphics 25, 3 (2006), pp. 569-578. http://dx.doi.org/10.1145/1141911.1141925LEVOY M., PULLI K., CURLESS B., RUSINKIEWICZ S., KOLLER D., PEREIRA L., GINZTON M., ANDERSON S., DAVIS J., GINSBERG J., SHADE J., FULK D. (2000): "The Digital Michelangelo Project: 3D scanning of large statues". In SIGGRAPH 2000, Computer Graphics Proceedings (July 24-28, 2000), Annual Conference Series, AddisonWesley, pp. 131-144. http://dx.doi.org/10.1145/344779.344849SCOPIGNO, Roberto et al. (2011): "Sampled 3D models for CH: beyond plain visualization", IEEE Computer, IEEE Press, July-Aug. 2011, (in press).STANCO F., BATTIATO S., GALLO G., (ed.) (2011): "Digital Imaging for Cultural Heritage Preservation". Taylor & Francis Group, 2011.TOLER-FRANKLIN C., BROWN B., WEYRICH T., FUNKHOUSER T., RUSINKIEWICZ S. (2010): "Multi-feature matching of fresco fragments". ACM Trans. Graphics (Proc. SIGGRAPH Asia) 29, 6 (2010), pp. 185-197. http://dx.doi.org/10.1145/1882262.1866207http://dx.doi.org/10.1145/1882261.186620

Virtual restoration and visualization changes through light: A review

This article belongs to the Special Issue Optical Technologies Applied to Cultural Heritage.The virtual modification of the appearance of an object using lighting technologies has become very important in recent years, since the projection of light on an object allows us to alter its appearance in a virtual and reversible way. Considering the limitation of non-contact when analysing a work of art, these optical techniques have been used in fields of restoration of cultural heritage, allowing us to visualize the work as it was conceived by its author, after a process of acquisition and treatment of the image. Furthermore, the technique of altering the appearance of objects through the projection of light has been used in projects with artistic or even educational purposes. This review has treated the main studies of light projection as a technique to alter the appearance of objects, emphasizing the calibration methods used in each study, taking into account the importance of a correct calibration between devices to carry out this technology. In addition, since the described technique consists of projecting light, and one of the applications is related to cultural heritage, those studies that carry out the design and optimization of lighting systems will be described for a correct appreciation of the works of art, without altering its state of conservationThis work has been funded by project number RTI2018-097633-A-I00 of the Ministry of Science and Innovation of Spain, entitled 'Photonic restoration applied to cultural heritage: Application to Dali's painting: Two Figures.

A Survey of Geometric Analysis in Cultural Heritage

We present a review of recent techniques for performing geometric analysis in cultural heritage (CH) applications. The survey is aimed at researchers in the areas of computer graphics, computer vision and CH computing, as well as to scholars and practitioners in the CH field. The problems considered include shape perception enhancement, restoration and preservation support, monitoring over time, object interpretation and collection analysis. All of these problems typically rely on an understanding of the structure of the shapes in question at both a local and global level. In this survey, we discuss the different problem forms and review the main solution methods, aided by classification criteria based on the geometric scale at which the analysis is performed and the cardinality of the relationships among object parts exploited during the analysis. We finalize the report by discussing open problems and future perspectives