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Proceedings Paper

Signal processing and analyzing works of art
Author(s): Don H. Johnson; C. Richard Johnson; Ella Hendriks
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Paper Abstract

In examining paintings, art historians use a wide variety of physico-chemical methods to determine, for example, the paints, the ground (canvas primer) and any underdrawing the artist used. However, the art world has been little touched by signal processing algorithms. Our work develops algorithms to examine x-ray images of paintings, not to analyze the artist's brushstrokes but to characterize the weave of the canvas that supports the painting. The physics of radiography indicates that linear processing of the x-rays is most appropriate. Our spectral analysis algorithms have an accuracy superior to human spot-measurements and have the advantage that, through "short-space" Fourier analysis, they can be readily applied to entire x-rays. We have found that variations in the manufacturing process create a unique pattern of horizontal and vertical thread density variations in the bolts of canvas produced. In addition, we measure the thread angles, providing a way to determine the presence of cusping and to infer the location of the tacks used to stretch the canvas on a frame during the priming process. We have developed weave matching software that employs a new correlation measure to find paintings that share canvas weave characteristics. Using a corpus of over 290 paintings attributed to Vincent van Gogh, we have found several weave match cliques that we believe will refine the art historical record and provide more insight into the artist's creative processes.

Paper Details

Date Published: 8 September 2010
PDF: 9 pages
Proc. SPIE 7798, Applications of Digital Image Processing XXXIII, 77980G (8 September 2010); doi: 10.1117/12.862994
Show Author Affiliations
Don H. Johnson, Rice Univ. (United States)
C. Richard Johnson, Cornell Univ. (United States)
Ella Hendriks, Van Gogh Museum (Netherlands)


Published in SPIE Proceedings Vol. 7798:
Applications of Digital Image Processing XXXIII
Andrew G. Tescher, Editor(s)

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