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NAME:PhD defence C.R. Johnson
METHOD:PUBLISH
BEGIN:VEVENT
DTSTART:20260511T094500
DTEND:20260511T111500
DTSTAMP:20260511T094500
UID:phd-defence-c-r-johnson@8F96275E-9F55-4B3F-A143-836282E12573
CREATED:20260921T135350
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SUMMARY:PhD defence C.R. Johnson
X-ALT-DESC;FMTTYPE=text/html: <html> <body> <p><p>Advances in Computat
 ional Art Connoisseurship</p></p> <p>Basic digital image processing i
 s an underexploited computational tool in the incorporation of digita
 l technology into art history research. This thesis covers a pioneeri
 ng effort undertaken since 2007 addressing the closure of this gap. T
 he path taken was the development of digital image processing methods
  to identify matching patterns in art supports and apply the data vis
 ualizations produced to art historical connoisseurial studies of fift
 eenth- to nineteenth-century European paintings on canvas and to fift
 eenth- to seventeenth-century European prints, drawings, and manuscri
 pts on laid paper. The software developed produces striped maps of ca
 nvas thread density that have been used to identify canvas from the s
 ame roll, principally for the paintings of Vincent van Gogh and Johan
 nes Vermeer, and watermark overlays that confirm exact matches indica
 tive of sheets of paper made on the same mold, principally among the 
 prints of Rembrandt van Rijn, the codices of Leonardo da Vinci, and s
 eventeenth-century Dutch drawings. These new digital tools have provi
 ded significant insights into the attribution and dating of paintings
  and the dating of drawings.</p><p>More information on the <a href="h
 ttps://hdl.handle.net/1871.1/e52ce578-043b-49db-b1a9-dd1b0c9ee5a8" da
 ta-new-window="true" target="_blank" rel="noopener noreferrer">thesis
 </a></p> </body> </html>
DESCRIPTION: Advances in Computational Art Connoisseurship Basic digit
 al image processing is an underexploited computational tool in the in
 corporation of digital technology into art history research. This the
 sis covers a pioneering effort undertaken since 2007 addressing the c
 losure of this gap. The path taken was the development of digital ima
 ge processing methods to identify matching patterns in art supports a
 nd apply the data visualizations produced to art historical connoisse
 urial studies of fifteenth- to nineteenth-century European paintings 
 on canvas and to fifteenth- to seventeenth-century European prints, d
 rawings, and manuscripts on laid paper. The software developed produc
 es striped maps of canvas thread density that have been used to ident
 ify canvas from the same roll, principally for the paintings of Vince
 nt van Gogh and Johannes Vermeer, and watermark overlays that confirm
  exact matches indicative of sheets of paper made on the same mold, p
 rincipally among the prints of Rembrandt van Rijn, the codices of Leo
 nardo da Vinci, and seventeenth-century Dutch drawings. These new dig
 ital tools have provided significant insights into the attribution an
 d dating of paintings and the dating of drawings.More information on 
 the <a href="https://hdl.handle.net/1871.1/e52ce578-043b-49db-b1a9-dd
 1b0c9ee5a8" data-new-window="true" target="_blank" rel="noopener nore
 ferrer">thesis</a>
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