• DocumentCode
    2794737
  • Title

    Matching canvas weave patterns from processing x-ray images of master paintings

  • Author

    Johnson, Don H. ; Sun, Lucia ; Johnson, C. Richard, Jr. ; Hendriks, Ella

  • Author_Institution
    Elec.&Comp. Eng., Rice Univ., Houston, TX, USA
  • fYear
    2010
  • fDate
    14-19 March 2010
  • Firstpage
    958
  • Lastpage
    961
  • Abstract
    Thread counting algorithms seek to determine from x-ray images the vertical and horizontal thread counts (frequencies) of the canvas weave comprising a painting´s support. Our spectral-based algorithm employs a variant of short-time Fourier analysis to the image domain that reveals isolated peaks at the proper vertical and horizontal frequencies. Paintings made on canvas sections cut from the same canvas roll have been hypothesized to have similar, distinctive weave characteristics, allowing art historians to more accurately date paintings. Spatial variation of weave frequency measurements across a painting were cross-correlated using a new measure to determine possible common weave patterns between pairs of x-rays. By analyzing a database of x-rays made from 180 paintings by van Gogh, our algorithms confirmed situations where paintings were known to have been made on canvases cut from the same roll and found new ones.
  • Keywords
    Fourier transforms; X-ray imaging; art; image matching; X-ray image processing; canvas weave patterns; master paintings; short-time Fourier analysis; spectral-based algorithm; thread counting algorithms; van Gogh; weave frequency measurements; Algorithm design and analysis; Art; Data analysis; Frequency measurement; Image analysis; Painting; Pattern matching; Spatial databases; X-ray imaging; art forensics; maximal linear correlation; thread counting; x-ray image processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
  • Conference_Location
    Dallas, TX
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4244-4295-9
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2010.5495297
  • Filename
    5495297