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We describe a computational technique for digitally authenticating
works of art. This approach builds statistical models of an artist
from a set of authenticated works. Additional works are then
authenticated against this model. The statistical model consists of
first- and higher-order wavelet statistics. We show preliminary
results from our analysis of thirteen drawings by Pieter Bruegel the
Elder. We also present preliminary results showing how these
techniques may be applicable to determining how many hands contributed
to a single painting.
Bibliographic citation for this report: [plain text] [BIB] [BibTeX] [Refer]
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Siwei Lyu, Daniel Rockmore, and Hany Farid, "Digital Art Forensics." Dartmouth Computer Science Technical Report TR2003-466, June 2003.
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