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Multi-Dimensional Analysis of An Oil Painting Center of Imaging Science Rochester Institute of Technology Pano Spiliotis May 7,1999
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Overview Background Procedure Results Evaluation of data Conclusion
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Background Multi-dimensional segmentation. –Using image capturing protocols and multi- dimensional segmentation, artifacts that are present in works of art will be easily identified. New approach in finding artifacts in oil paintings.
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Overview Background Procedure Results Evaluation of data Conclusion
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Camera Setup Monochrome CCD camera Ultraviolet Black Light (Blue light) Tungsten Light Source Infrared Filter Important that images are in registration.
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Illumination Three types –Ultraviolet –Visible –Infrared
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Ultraviolet Illumination – New Varnish – Over-painting
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Visible Illumination Topographical Inspection – Canvas Repair – Buckling of Canvas – Over-painting
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Infrared Illumination Infrared filter is presented to the system. –Under-drawing –Areas that are not present in the UV and VIS.
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Flat Fielding Procedure taking a non-uniformly illuminated image and resulting in an evenly illuminated image. non-uniformly illuminated image Flat-fielded image
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Image Segmentation Looking for common areas. Segmentation of a common area. Trial and error. Save common area as an image and pixel value.
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Overview Background Procedure Results Evaluation of data Conclusion
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Results Visible image Infrared image Ultraviolet image
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2-D Segmentation Program Visible Image Infrared Image Visible Image Infrared Image
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Pseudo Coloring Visible Image Infrared Image
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After Segmentation Visible Image Infrared Image Visible Image Infrared Image
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Overview Background Procedure Results Evaluation of data Conclusion
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Evaluation of results Areas that have been segmented reveal artifacts. John Sutton, Associate Conservator from The West Lake Conservators, was called in to prove these findings. The halo is not the original halo painted.
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Conclusion Research proved to be successful. 2-D Segmentation provides art conservator’s with a tool to validate their discoveries.
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