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With museums increasingly digitizing their art collections, it becomes pretty easy to forge paintings. Now, two researchers are working on a digital system to help detect original works from counterfeit ones. The findings of the study, which was led by James Z. Wang, associate professor of information sciences and technology, Jia Li, associate professor of statistics, were based on 101 high-resolution greyscale scans of Van Gogh paintings provided by the Van Gogh and Kroller-Muller Museums in the Netherlands. Wang and Li broke each scan down into sections measuring 512 by 512 pixels, or about 2.5 by 2.5 inches in canvas size, and analysed them based on patterns and geometric characteristics of the brush strokes. From the 101 scans received from the museums, art historians identified 23 as unquestionably authentic Van Gogh works. These were used by the computer system as a training database for Van Gogh’s brushstroke styles. Statistical models were created to capture the unique style, or ‘handwriting,’ that became the artist’s signature in 23 of the scans. The other 78 - either works of Van Gogh, works of Van Gogh’s peers or paintings that had at one time been attributed to him but later found to be unauthentic - were compared against the generated models to test the algorithms. Wang and Li, along with
computer science and engineering doctoral student Weina Ge, compiled
those findings into an online system that allows any painting to be
compared against existing data to help determine The painting analysis project results were first presented at a workshop at the Van Gogh Museum in May 2007. The study "Image processing for artist identification: Computerised analysis for Vincent Van Gogh’s painting brushstrokes" has been published in the July issue of IEEE Signal Processing. — ANI
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