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This paper introduces the Watermark Imaging System (WImSy) which can be used to photograph, document, and study sheets of paper. The WImSy provides surface images, raking light images, and transmitted light images of the paper, all in perfect alignment. We develop algorithms that exploit this alignment by combining several images together in a process that mimics both the “surface image removal” technique and the method of “high dynamic range” photographs. An improved optimization criterion and an automatic parameter selection procedure streamline the process and make it practical for art historians and conservators to extract the relevant information to study watermarks. The effectiveness of the method is demonstrated in several experiments on images taken with the WImSy at the Metropolitan Museum of Art in New York and at the Getty Museum in Los Angeles, and the results are compared with manually optimized images.

Reflectance Transformation Imaging (RTI) is a non-invasive method of examination which can be used to document and visualize the surface texture of objects, including artworks. Through imaging an object under different directions of illumination, topographical maps of a low relief surface can be produced, which when further processed can be used as an interactive visual aid. This paper summarizes the current state of research on micro-RTI, and presents an investigation into a micro-RTI system comprised of a digital microscope and miniature lighting array dome, which was originally developed to study small areas of surface texture. The article reviews the techniques required to adequately use the micro-RTI, and evaluates the system’s use as a practical tool for conserving and documenting modern and contemporary easel paintings. This was determined by evaluating its data processing, ability to accurately document test panels and case study paintings, and comparing it with alternative documentation methods of standard microscopy and laser scanning. It was found that micro-RTI is a useful tool for modern and contemporary paintings and their often complex and/or delicate surfaces, where subtle surface alterations can result in visually distracting features.

1 The aim of the present work is to assess similarities between papers used in a collection of 215 lithographs by Henri Matisse. It combines the use of an anisotropic multiscale analysis built upon the hyperbolic wavelet transform to compute distances between textures, with the fact that four textures of the same print were digitized, corresponding to four different (recto/verso and top/side) views. A permutation algorithm is devised showing the importance of reordering the four views to achieve a meaningful comparison across the papers, thus suggesting possibly different artistic intentions in some prints.

This cover collaboration explores the photography of Bill Brandt (1904–1983) from the perspective of the physical print, drawing attention to its material qualities and practical functions. The small sampling presented here captures some of Brandt’s major visual themes, beginning with his socio-political images of wartime Britain through to his more subjective engagement with landscape and art in the post-war decades. This shift is often seen in terms of Brandt’s career path—from photojournalist in the 1930s and 1940s, to art world photographer in the post-war era. Brandt’s stature as an artist came onto assured footing in the 1960s, with exhibitions at the Museum of Modern Art, New York, in 1961 and 1969, and commercial representation by Marlborough Gallery in the 1970s.1 While Brandt began to print to meet these new expectations, he did not abandon the long-standing practices and interests of his early career: his commitment to the reproduction of photographs on the printed page. Newsprint illustrations and bookplates remained his primary expressive channels. Between 1936 and the year of his death, Brandt published at least one photo-book per decade, as well as contributing dozens of photo-essays and hundreds of individual photographs to illustrated magazines.

Throughout his career, László Moholy-Nagy (1895–1946) produced many photograms, a selection of which was examined in European and American collections. Sheet dimensions and thickness, base color, surface gloss and texture were recorded. The analysis of the data and the results of this investigation are presented in this article. The article also explores the effectiveness of paper characterization and how it can contribute to and enhance historical research when applied to a particular body of work by one artist.

International audience; As part of the Historic Photographic Paper Classification Challenge, a multitude of approaches to quantifying paper texture similarity have been developed. These approaches have yielded encouraging results when applied to very controlled datasets containing photomicrographs of familiar specimens. In this paper, we report on the k-nearest neighbors classification performance of two multiscale analysis-based texture similarity approaches when applied to a much larger reference collection of silver gelatin photographic papers. The clusters for this data set were derived from a visual sorting experiment conducted by art conservators and paper experts later extended through crowd-sourcing. The results show that these texture similarity approaches, when combined with a simple k-nearest neighbors classification algorithm, yield workable performances with accuracy of up to 69%. We discuss this outcome in the context of available data and the cross-validation procedure used, then provide suggestions for improvement.

The Watermark Imaging Box (WImBo) Project is an inter-institutional collaboration to develop a low-cost, portable system for imaging watermarks and chain lines in papers, with a special focus on the prints of Rembrandt van Rijn (Dutch, 1606–1669) and his pupils. Representative of paper available in seventeenth-century Europe, Rembrandt's papers show a range of physical features that are typically documented using a variety of imaging techniques. Building on this base, computational analysis of Rembrandt's papers has demonstrated great potential for enhancing existing scholarship by discovering affinities among prints across collections. However, a widely distributed imaging campaign poses challenges, some of which derive directly from the nature of Rembrandt's prints and papers, including passages of heavy ink application. To develop and refine new approaches for large-scale distributed imaging, WImBo teams were supplied with carefully selected and prepared test papers.

Summary Surface textures of a large collection of photographic papers dating from 1896 to the present were measured using a laser scanning confocal microscope (LSCM) with four different objective lenses. Roughness characterization parameters were calculated from the texture measurements and were compared with gloss measurements. Characterization by the area-scale fractal dimension (Das) and the area-scale fractal complexity (Asfc) provided the strongest correlations between gloss reflectance and surface texture. The measurements with the 5× and 10× objectives, which contained many large-scale, spiky measurement artifacts that distorted the measurement, resulted in the strongest correlations (R2 > 0.8) compared to the 20× and 50× (R2

Historical references of silver gelatin photographic paper sheet size and thickness were collected to determine standardized dimensions in use during the 20th century. A total of 32 sizes and three thicknesses were determined to be de facto standards. Despite periodic attempts to create international standards, manufacturers of photographic paper resisted broad standardization and instead relied on traditional and aesthetic norms, many dating back to the origins of photography. Five aspect ratios were found to dominate these sizes, implying that image scaling was a major factor for determining dimensions. By contrast, standards that emerged from the papermaking industry had a small impact on sizes of silver gelatin paper. The identified de facto standards were distilled from a larger population of great diversity, with numerous non-standard sizes appearing and disappearing over time. This diversity is less pervasive with regard to thickness, with single and double weight sizes dominating throughou...

Surface texture is a critical feature in the manufacture, marketing, and use of photographic paper. Raking light reveals texture through a stark rendering of highlights and shadows. Though close-up raking light images effectively document surface features of photographic paper, the sheer number and diversity of textures used for historic papers prohibits efficient visual classification. This work provides evidence that automatic, computer-based classification of texture documented with raking light is feasible by demonstrating an encouraging degree of success sorting a set of 120 images made from samples of historic silver gelatin paper. Using this dataset, four university teams applied different image-processing strategies for automatic feature extraction and degree of similarity quantification.All four approaches successfully detected strong affinities and outliers built into the dataset. The creation and deployment of the algorithms was carried out by the teams without prior knowledge of the distributions of similarities and outliers.These results indicate that automatic classification of silver gelatin photographic paper based on close-up texture images is feasible and should be pursued. To encourage the development of other classification schemes, the 120-sample “training” dataset used in this work is available to other academic researchers at http://www.PaperTextureID.org.

International audience; Wove paper, made on a papermaking screen or mold having a surface of smooth tightly woven wires, was the predominant paper type used for printing in the twentieth century. To aid in the study and classification of fine art prints on wove paper, the present work compares the results of five different image processing approaches for characterizing surface texture. Using a collection of popular wove papers, a reference dataset of raking light close-up images was assembled. Five research teams undertook their own processing strategies to detect affinities among the paper samples. Their success in identifying similarity groupings are reported.

Prior work on texture analysis of historic, photographic papers has focused primarily on measures of texture similarity. However, automated grouping or clustering of photographic paper textures in a way that is meaningful to art conservators remains an open problem. In this work a deep learning approach to automated classification is presented, for clusters derived from a human sorting experiment conducted by 19 art conservators and paper experts and subsequently extended through crowd-sourcing. The proposed approach uses a deep convolutional neural network, and results are presented on the performance in automatically classifying images when compared to human experts.

International audience; Texture characterization of photographic papers is likely to provide scholars with valuable information regarding artistic practices. Currently, texture assessment remains mostly based on visual and manual inspections, implying long repetitive tasks prone to inter- and even intra-observer variability. Automated texture characterization and classification procedures are thus important tasks in historical studies of large databases of photographic papers, likely to provide quantitative and reproducible assessments of texture matches. Such procedures may, for instance, produce vital information on photographic prints of uncertain origins. The hyperbolic wavelet transform, because it relies on the use of different dilation factor along the horizontal and vertical axes, permits to construct robust and meaningful multiscale and anisotropic representation of textures. In the present contribution, we explore how unsupervised clustering strategies can be complemented both to assess the significance of extracted clusters and the strength of the contribution of each texture to its associated cluster. Graph based filterbank strategies are notably investigated with the aim to produce small size significant clusters. These tools are illustrated at work on a large database of about 2500 exposed and non exposed photographic papers carefully assembled and documented by the MoMA and P. Messier's foundation. Results are commented and interpreted.

International audience; Texture characterization of photographic prints can provide scholars with valuable information regarding photographers? aesthetic intentions and working practices. Currently, texture assessment is strictly based on the visual acuity of a range of scholars associated with collecting institutions, such as museum curators and conservators. Natural interindividual discrepancies, intraindividual variability, and the large size of collections present a pressing need for computerized and automated solutions for the texture characterization and classification of photographic prints. In the this article, this challenging image processing task is addressed using an anisotropic multiscale representation of texture, the hyperbolic wavelet transform (HWT), from which robust multiscale features are constructed. Cepstral distances aimed at ensuring balanced multiscale contributions are computed between pairs of images. The resulting large-size affinity matrix is then clustered using spectral clustering, followed by a Ward linkage procedure. For proof of concept, these procedures are first applied to a reference data set of historic photographic papers that combine several levels of similarity and second to a large data set of culturally valuable photographic prints held by the Museum of Modern Art in New York. The characterization and clustering results are interpreted in collaboration with art scholars with an aim toward developing new modes of art historical research and humanities-based collaboration.

Digital imaging and signal processing technologies offer new, quantitative methods to classify and characterize surface textures. This paper presents a collaborative project to systematically and semi-automatically characterize the surface texture of traditional black and white photographic paper as well as contemporary photographic inkjet printing media. Surface texture is a critical feature in the manufacture, marketing and use of photographic papers, especially those used for fine art printing. Raking light reveals texture through a stark rendering of highlights and shadows. Though raking light images effectively document surface features of paper, the sheer number and diversity of textures prohibits efficient visual classification. This work provides evidence that automatic, computer-based classification of texture documented with raking light is feasible by demonstrating an encouraging degree of success sorting two sets of 120 close-up images made from diverse samples of inkjet paper and canvas available in the market from 2000 through 2011 as well as historic samples of black and white paper made at different times during the 20th century The samples used for this study were drawn from two prominent reference collections of photographic media: the Wilhelm Analog and Digital Color Print Materials Reference Collection and Paul Messier's reference collection of historic black and white (silver gelatin) papers. Using these two datasets, four university teams applied different image processing strategies for automatic feature extraction and degree of similarity quantification. All four approaches were successful in detecting strong affinities among similarity groupings built into the datasets as well as identifying outliers. The creation and deployment of the algorithms was carried out by the teams without prior knowledge of the distributions of similarities and outliers. These results indicate that automatic classification of photographic paper based on texture images is feasible. To encourage the development of additional classification schemes, the two “training” datasets used in this work (comprising 240 images) is available to other academic researchers at www.PaperTextureID.org.)

A reference collection of mostly 20th-century photographic paper was surveyed for the presence of optical brightening agents. Only fiber-based, gelatin silver paper was assessed. In all, 1,804 samples were examined, dating from 1896 to 2004 and representing 40 different manufacturers. No optical brightening agents were found in samples dating from 1896 to 1949. The first occurrence of optical brightening agent was found in samples dating between 1950 and 1954. Between 1955 and 1964, the frequency of occurrence for optical brightening agents increased rapidly. Toward the latter part of this date range the occurrence of optical brighteners rose, with 70% of all samples showing brighteners. Between 1965 and 1979, occurrence of optical brightening agents declined to a low of 39% of all samples. A marked increase in occurrence was observed after 1980, when 81% of samples exhibited optical brightening agents. These results indicate that a significant proportion, and for some time periods a significant m...

This paper presents a methodology for the examination and documentation of a videobased installation as applied to Dara Birnbaum's 1989–90 Tiananmen Square: Break-In Transmission. Functional and aesthetic roles of compositional elements and electronic components are characterized. Background on relevant technologies is summarized. The results of the assessment indicate that the stability of the piece may be threatened due to media degradation, format obsolescence, hardware obsolescence, and a lack of centralized documentation. Recommendations for near-term and long-term preservation activities are offered. This article is a result of TechArchaeology: A Symposium on Installation Art Preservation.

Daguerreotypes were the first form of photographs and were popular between 1840 and 1860, after which they were superseded by more modern techniques. The daguerreotype image is composed of silver/mercury microcrystals of varying size and density on a silver-coated copper substrate. Nineteenth century daguerreotypes, over the intervening 140 years, have suffered degradation and oxidation, which has greatly reduced their historic and artistic value. Laser ablation techniques have been previously explored for use in the characterization, dating, and restoration of historic paintings, parchments, stained glasses, and statues. We report here the use of a number of modern surface science techniques (especially those using lasers, mass spectrometry, and microscopy) to characterize and analyze both normal and degraded daguerreotypes. Then, attempts to use laser ablation techniques for cleaning and restoring damaged nineteenth century samples will be described. The optimal wavelength, pulse length, pulse energy, and focussing conditions are critical for effective cleaning while preventing damage to the fragile image.

Laser desorption mass spectroscopy has been used to characterize both modern and ∼ 150-year-old daguerreotypes. Such investigations are a necessary prelude to attempts to clean them of tarnish and other contaminants by laser ablation of the surface layers. Both positive- and negative-ion time-of-flight spectra were obtained following YAG laser ablation/desorption at 1064, 532, and 355 nm. Major peaks obtained from several daguerreotypes reveal expected elements from the substrate (Ag, Cu) as well as the developing (Hg) and gilding (Au) processes. Silver clusters (Ag n) may reflect surface desorption of molecules or, alternatively, aggregates formed in the ejection process. Silver sulfide molecules observed from old daguerreotypes are the signature of the tarnishing process.

Current conservation practice often calls for aqueous surface cleaning, unmounting and washing of albumen photographs. This research is intended as an assessment of this common treatment technique which was a logical adaptation from paper conservation and photographic processing. Data are presented so that the conservator can better balance the possible benefits of aqueous treatment against the drawbacks. The results of this study show that any aqueous treatment, be it surface cleaning or immersion, increases the cracking of the albumen layer while not substantially altering albumen yellowing. This study is based upon the controlled aqueous treatment of a group of twenty mounted and never-mounted albumen photographs. Print color, gloss, and albumen cracking were measured before and after treatment with water. Color data shows that surface cleaning and immersion are not effective in altering image discoloration. Measurements of crack width and population were made by comparing microphotographs of cracks taken before treatment, after surface cleaning, and after immersion. All albumen prints exhibit some form of cracking prior to treatment. The pre-existing cracks in albumen photographs increase in width after surface cleaning and again after aqueous immersion. The number of cracks in a given area increases after treatment. The measurement of gloss before and after treatment shows that most prints decrease in gloss after treatment.

Fundamental physical and mechanical properties of albumen photographs were studied with the goal of explaining the tendency for pre-existing cracks in the albumen layer to increase in number and width when exposed to water. Samples were taken from the following materials: historical 19th-century albumen prints, unsized cotton paper, albumen prints made by the authors for the purpose of the study, albumen/paper composites, and 'bars' made by casting albumen in silicone grease troughs. The samples were subjected to a variety of tests, including stress-strain analysis, ultrasonic impediometry, and measuring before, during, and after exposure to humidity. The various materials that make up an albumen photograph respond differently to changes in relative humidity, leading to problems between the components. Care should be taken when treating albumen prints with either water or water vapor, and the conditions under which the prints are stored should be carefully considered.

The preservation of nineteenth-century albumen prints is of great concern to collection managers and to conservators of photographic materials. In the field of art conservation, preservation techniques incorporating aqueous treatments are often used to enhance the long- and short-term stability of historical artifacts or art objects. In a study of the interaction of water with albumen photographs, experiments were carried out in the ESEM to follow the real time effects of water on the prints. The experiments were designed to observe the effects of a range of relative humidities and liquid water on samples of expendable historic albumen prints, utilizing the advantages of imaging in the presence of water vapor. All albumen photographs exhibit a fine network of cracks in the albumen protein layer. Average crack width is approximately 10 μm. As observed in the ESEM, a 4.25-fold increase in the width of a single crack (at 50% RH), viewed normal to the surface, resulted from a single controlled excursion to high relative humidity and immersion. In an extraordinary series of images, a print viewed in cross-section exhibited a 22% swelling and shrinkage in thickness, and a 5% and 9% swelling and shrinkage along the width of a fragment of the albumen/image layer when the sample was immersed in water and dried. The visual information gained through the use of the ESEM helped to focus a materials investigation and served as a foundation for a study which shows that aqueous treatment causes increased cracking of both unsupported albumen and the albumen/image layer in prints. © 1993 Wiley-Liss, Inc.

Extended abstract of a paper presented at Microscopy and Microanalysis 2013 in Indianapolis, Indiana, USA, August 4 – August 8, 2013.

Laser ablation mass spectrometry and surface-enhanced Raman spectroscopy have been used to characterize both modern and 150 year old daguerreotypes. Such investigations are a necessary prelude to attempts to clean them of tarnish by laser ablation. A demonstration of the successful cleaning of a damaged daguerreotype is presented.

Laser desorption/abiation describes a process whereby an intense, pulsed laser beam interacts with a solid surface leading to the ejection of atoms, molecules, ions, clusters and macroscopic particles.1,2 Electromagnetic energy is converted to electronic, thermal, chemical and mechanical energy. The process is extremely complex since different mechanisms operate at different values of laser wavelength, pulse duration and intensity. In general, the term laser desorption is used when particle emission occurs with no visible microscopic alteration of the surface composition or structure. In contrast, laser ablation is a much more energetic phenomenon accompanied by high temperatures, gas dynamic effects, plasma formation and surface cratering. In practice, these two processes are not completely distinct, but reflect a continuum of physical effects indexed to the laser power density and various material properties.

International audience; Digital imaging and signal processing technologies offer new methods for inkjet and photographic media engineers and manufacturers, and those responsible for product quality control, to classify and characterize printing materials surface textures using new and more quantitative methods. This paper presents a collaborative project to systematically and semi-automatically characterize the surface texture of inkjet media. These methods have applications in product design and specification, and in manufacturing quality control. Surface texture is a critical feature in the manufacture, marketing and use of inkjet papers, especially those used for fine art printing. Raking light reveals texture through a stark rendering of highlights and shadows. Though raking light photomicrographs effectively document surface features of inkjet paper, the sheer number and diversity of textures prohibits efficient visual classification. This work provides evidence that automatic, computer-based classification of texture documented with raking light photomicrographs is feasible by demonstrating an encouraging degree of success sorting a set of 120 photomicrographs made from diverse samples of inkjet paper and canvas available in the market from 2000 through 2011. The samples used for this study were drawn from the Wilhelm Analog and Digital Color Print Materials Reference Collection. Using this dataset, four university teams applied different image processing strategies for automatic feature extraction and degree of similarity quantification. All four approaches were successful in detecting strong affinities among similarity groupings built into the dataset as well as identifying outliers. The creation and deployment of the algorithms was carried out by the teams without prior knowledge of the distributions of similarities and outliers. These results indicate that automatic classification of inkjet paper based on texture photomicrographs is feasible. To encourage the development of additional classification schemes, the 120 inkjet sample “training” dataset used in this work is available to other academic researchers at www.PaperTextureID.org.

International audience; From the point of view of graph signal processing, we show that spectral clustering is equivalent to an ideal low-pass filterbank. Building upon previous multiscale community detection ideas [11], and integrating the concept of community cores [8], we propose a data-driven filterbank-based classification method. We apply this method to the texture classification of photographic papers useful to art historians, and we show that it provides a richer and more informative description of the data’s structure in clusters.

International audience; Surface texture is a critical feature in the manufacture, marketing, and use of photographic paper. Raking light reveals texture through a stark rendering of highlights and shadows. Though close-up raking light images effectively document surface features of photographic paper, the sheer number and diversity of textures used for historic papers prohibits efficient visual classification. This work provides evidence that automatic, computer-based classification of texture documented with raking light is feasible by demonstrating an encouraging degree of success sorting a set of 120 images made from samples of historic silver gelatin paper. Using this dataset, four university teams applied different image-processing strategies for automatic feature extraction and degree of similarity quantification.All four approaches successfully detected strong affinities and outliers built into the dataset. The creation and deployment of the algorithms was carried out by the teams without prior knowledge of the distributions of similarities and outliers.These results indicate that automatic classification of silver gelatin photographic paper based on close-up texture images is feasible and should be pursued. To encourage the development of other classification schemes, the 120-sample “training” dataset used in this work is available to other academic researchers at http://www.PaperTextureID.org.; La textura superficial es un rasgo crítico en la manufactura, comercialización y uso de papel fotográfico. La luz rasante revela la textura a través de una representación nítida de áreas luminosas y sombras. A pesar de que las imágenes con luz rasante documentan efectivamente las características superficiales del papel fotográfico, la cantidad misma y la diversidad de texturas usadas en papeles históricos hace imposible una clasificación visual eficiente. Este trabajo proporciona evidencias de que la clasificación automática de la textura documentada con luz rasante, realizada por computadora es factible al demostrar un motivante grado de éxito al clasificar un grupo de 120 imágenes hechas de muestras de papel histórico de gelatina de plata. Usando esta base de datos, cuatro equipos universitarios aplicaron diferentes estrategias de procesamiento de imágenes para la extracción automática de rasgos y cuantificación del grado de similitud. Las cuatro estrategias detectaron con éxito afinidades fuertes así como los casos atípicos incluidos en la base de datos. Los equipos crearon y usaron algoritmos sin conocimiento previo de las similitudes y los casos lejanos al promedio. Estos resultados indican que la clasificación automática de papel fotográfico de gelatina de plata basada en imágenes que muestran acercamientos de la textura es viable y debería realizarse. Para incentivar el desarrollo de otros esquemas de clasificación el grupo de 120 muestras de “entrenamiento” usado en este trabajo está disponible para otros investigadores en http://www.PaperTextureID.org.; La texture de la surface du papier photographique est une caractéristique essentielle de sa fabrication, de sa commercialisation et de son utilisation. La lumière rasante révèle la texture du papier par un rendu saisissant des lumières et des ombres. Bien que les gros plans en lumière rasante documentent efficacement les caractéristiques de la surface des papiers photographiques, le nombre et la diversité des textures des papiers historiques empêchent une classification visuelle efficace. Le présent travail démontre que la classification automatique par ordinateur de textures documentées avec une lumière rasante est possible, en démontrant un degré encourageant de succès dans le tri d'un ensemble de 120 images réalisées à partir d'échantillons de papiers historiques au gélatino-bromure d'argent. À partir de ce groupe d'images, quatre équipes universitaires ont appliqué différentes stratégies de traitement d'image afin d'extraire automatiquement des caractéristiques et de quantifier le degré de similitude des papiers. Les quatre approches ont chacune réussi à détecter de fortes affinités, ainsi que des images avec caractéristique aberrante intégrées dans le groupe. La création et le déploiement des algorithmes ont été réalisés par les équipes sans connaissance préalable de la répartition des similitudes et des images aberrantes. Ces résultats indiquent que la classification automatique des papiers photographiques au gélatino-bromure d'argent basée sur des gros plans de texture est possible et doit être poursuivie. Pour encourager le développement d'autres systèmes de classification, les données des 120 échantillons utilisées dans ce travail sont mises à la disposition d'autres chercheurs scientifiques à l'adresse suivante: http://www.PaperTextureID.org.