Paul Messier

PURSUING AUTOMATED CLASSIFICATION OF HISTORIC PHOTOGRAPHIC PAPERS FROM RAKING LIGHT IMAGES

Abstract 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.

Multiscale Anisotropic Texture Analysis and Classification of Photographic Prints: Art scholarship meets image processing algorithms

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.

Effects of aqueous treatment on albumen photographs

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.

OPTICAL BRIGHTENING AGENTS IN PHOTOGRAPHIC PAPER

Abstract 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 majority, of black-and-white, paper-based photographs made after the early 1950s contain optical brightening agents. This finding has implications for the treatment and display of photographs, as the presence of optical brightening agents is not routinely documented and the effects of storage environment, display, and treatment are poorly understood.

Multiscale Anisotropic Texture Unsupervised Clustering for Photographic Paper

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. Messiers foundation. Results are commented and interpreted.

Correlation between gloss reflectance and surface texture in photographic paper

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 (R(2)  > 0.8) compared to the 20× and 50× (R(2)  < 0.5). The presence of spiky artifacts in the measurements, which increases when the magnification of the objective lens is decreased, appears to amplify surface features in such a way to improve the correlations.

Automated surface texture classification of photographic print media

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 Messiers 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.).

PHOTOGRAPHIC PAPER XYZ: DE FACTO STANDARD SIZES FOR SILVER GELATIN PAPER

Abstract 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 throughout the century and a medium weight option gaining ground after the 1940s. In all cases, the three dimensions of a finished photograph, X, Y, and Z, reflect practical and aesthetic decision-making. When compared with the de facto standards determined in this research, these dimensions can provide insight into the working practice and intentions of photographers.

Dara Birnbaum's Tiananmen Square: Break-In Transmission: A Case Study in the Examination, Documentation, and Preservation of a video-Based Installation

Abstract This paper presents a methodology for the examination and documentation of a videobased installation as applied to Dara Birnbaums 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.

Wove paper analysis through texture similarities

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.