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Thursday, May 16 • 3:30pm - 4:00pm
01. Comparison of Image Processing Techniques to Evaluate the Cleaning Efficiency of Gecko Microdusters on Acrylic Paint Surfaces

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This poster compares two methods that can be used to evaluate the cleaning abilities of gecko microdusters to remove dust from an acrylic painted canvas compared to other traditional dry cleaning methods (i.e cosmetic sponge, brush, etc). Gecko microdusters are micro scale tubular structures made from a PDMS polymer (polydimethylsiloxane). They non-destructively clean paintings by generating a van der Waals attraction between the pillars and the dust on a canvas. This adhesion allows for the removal of dust without the need to sweep or scrape it off the canvas. These actions, used in other cleaning methods, have shown to create microscopic scratches and scrapes due to moving the dust around on the canvas. This same interaction is observed when geckos make surface contact with objects they walk on. The image processing technique comparison is another step in developing a new cleaning method to reduce damage inflicted on acrylic paintings during treatment and to ensure that the conservation process maintains the standard of being as non-destructive as possible. A small strip of acrylic painted canvas is soiled with fluorescent silica particles, used to simulate dust, to represent a painting accumulating dust over a period of time. UV fluorescence images are taken of each sample: a DSLR camera with a UV-blocking filter captures images of samples under UV light before soiling, after soiling, and after cleaning for each sample at the same exposure.

In the first method for evaluating cleaning efficiency, the histogram data for each sample’s images are used to calculate a number proportional to the total amount of fluorescence detected by the camera, which is assumed to be proportional to the amount of dust remaining on the surface. In the second method a particle-counting algorithm, based on a series of operations in the software ImageJ, is used to calculate the total number of dust particles remaining on the surface. The results of the two measurements are then plotted against each other, total histogram count versus particle number, to observe the regimes in which each method is effective. This comparison shows that when analyzing samples with a low amount of fluorescence/soiling, both methods are effective, though at very low soiling levels particle counting may be advantageous. The histogram method is more reliable when there is a high amount of fluorescence/soiling. Overall, both image processing demonstrates the advantage of using a diverse approach to interpreting image data.

Speakers
avatar for Genevieve Antoine

Genevieve Antoine

Post-grad Associate, Institute for the Preservation of Cultural Heritage, Yale University
Genevieve Antoine is a recent graduate of Tuskegee University where she earned a Bachelors of Science in Chemistry and in Physics. She became interested in working within the museum field after attending the HBCU Summer Teacher`s Institute in Technical Art History at Yale University... Read More →

Co-Author
avatar for Cynthia Schwarz

Cynthia Schwarz

Associate Conservator of Paintings, Yale University Art Gallery
Cynthia Schwarz is the Associate Conservator of Paintings at the Yale University Art Gallery. Her research interests include the structural treatment of canvas paintings, the conservation of 19th- and 20th-century American murals, and how advances in microbiology can aid in materials... Read More →
avatar for Pablo Londero

Pablo Londero

Conservation Scientist, Yale University
Pablo Londero has worked as a conservation scientist for six years. He received his Ph.D. in physics from the University of Rochester in 2005, specializing in quantum and nonlinear optical physics. He has held the position of Research Associate at The Metropolitan Museum of Art and... Read More →


Thursday May 16, 2019 3:30pm - 4:00pm EDT
Uncas Ballroom Foyer Sky Convention Center, Mohegan Sun