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Monday, June 25, 2012 begins a new, 8-week, O’Keeffe Museum Conservation Program summer preservation project. This year, thanks to the generous financial support of the National Center For Preservation Technology and Training (http://ncptt.nps.gov/ ), The Stockman Family Foundation and New Mexico AmeriCorps Cultural Technology community service program, we will be testing three, exciting, new technologies in “Computational Imaging”.

In conservation and preservation, computational imaging uses the power of today’s laptop microprocessors and digital cameras to create accurate, archival, 3-D images and documentation for artistic and cultural objects. From the microscopic texture of a paint brush-stroke to the undulating pitch and volume of a historic adobe wall, computational imaging can document and help monitor the changes in three-dimensional shape, size and deterioration of the historic properties and objects under the care of the Georgia O’Keeffe Museum. Since we preserve, document and monitor everything from historic landscapes and historic structures to O’Keeffe’s paintings, pastels and drawings to the tiny snail and scallop shells she collected and imaged in her art, automating and increasing the accuracy of our documentation and measurements can help us get better work done, more systematically, and in less time.

New Mexico AmeriCorps Cultural Technology (NM-ACT) interns Joey Montoya of Espanola and Greg Williamson of Santa Fe will join Head of Conservation Dale Kronkright and Assistant Registrar Darrah Wills in testing three imaging processes: Reflectance Transformation Imaging, Stereo Photogrammetry and Structured Light Imaging. Each uses different algorithms to construct detailed 3-D images and data by assembling regular, 2-D digital photographs.

To make the documentation useful from a scientific perspective, the source photographic conditions, resolution and algorithmic processing pathways must be carefully documented in a digital “lab notebook”. Further, to facilitate the accurate computer comparison of 3-D features of a painting, door, window or landscape over time – to determine if features are subtly changing in ways that indicate underlying deterioration or damage – the algorithms must be able to recognize and compare L*A*B* feature data in photographs that have been taken years or decades later with different cameras, different lighting conditions and slightly different orientations. These conditions are pretty demanding!

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