BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Vrije Universiteit Amsterdam//NONSGML v1.0//EN
NAME:PhD defence C.R. Johnson
METHOD:PUBLISH
BEGIN:VEVENT
DTSTART:20260511T094500
DTEND:20260511T111500
DTSTAMP:20260511T094500
UID:2026/phd-defence-c-r-johnson@8F96275E-9F55-4B3F-A143-836282E12573
CREATED:20260602T173852
LOCATION:(1st floor) Auditorium, Main building De Boelelaan 1105 1081 HV Amsterdam
SUMMARY:PhD defence C.R. Johnson
X-ALT-DESC;FMTTYPE=text/html: <html> <body> <p>Advances in Computation
 al Art Connoisseurship</p> <p>Basic digital image processing is an un
 derexploited computational tool in the incorporation of digital techn
 ology into art history research. This thesis covers a pioneering effo
 rt undertaken since 2007 addressing the closure of this gap. The path
  taken was the development of digital image processing methods to ide
 ntify matching patterns in art supports and apply the data visualizat
 ions produced to art historical connoisseurial studies of fifteenth- 
 to nineteenth-century European paintings on canvas and to fifteenth- 
 to seventeenth-century European prints, drawings, and manuscripts on 
 laid paper. The software developed produces striped maps of canvas th
 read density that have been used to identify canvas from the same rol
 l, principally for the paintings of Vincent van Gogh and Johannes Ver
 meer, and watermark overlays that confirm exact matches indicative of
  sheets of paper made on the same mold, principally among the prints 
 of Rembrandt van Rijn, the codices of Leonardo da Vinci, and seventee
 nth-century Dutch drawings. These new digital tools have provided sig
 nificant insights into the attribution and dating of paintings and th
 e dating of drawings.</p><p>More information on the <a href="https://
 hdl.handle.net/1871.1/e52ce578-043b-49db-b1a9-dd1b0c9ee5a8" data-new-
 window="true" target="_blank" rel="noopener noreferrer">thesis</a></p
 > </body> </html>
DESCRIPTION: Basic digital image processing is an underexploited compu
 tational tool in the incorporation of digital technology into art his
 tory research. This thesis covers a pioneering effort undertaken sinc
 e 2007 addressing the closure of this gap. The path taken was the dev
 elopment of digital image processing methods to identify matching pat
 terns in art supports and apply the data visualizations produced to a
 rt historical connoisseurial studies of fifteenth- to nineteenth-cent
 ury European paintings on canvas and to fifteenth- to seventeenth-cen
 tury European prints, drawings, and manuscripts on laid paper. The so
 ftware developed produces striped maps of canvas thread density that 
 have been used to identify canvas from the same roll, principally for
  the paintings of Vincent van Gogh and Johannes Vermeer, and watermar
 k overlays that confirm exact matches indicative of sheets of paper m
 ade on the same mold, principally among the prints of Rembrandt van R
 ijn, the codices of Leonardo da Vinci, and seventeenth-century Dutch 
 drawings. These new digital tools have provided significant insights 
 into the attribution and dating of paintings and the dating of drawin
 gs. More information on the <a href="https://hdl.handle.net/1871.1/e5
 2ce578-043b-49db-b1a9-dd1b0c9ee5a8" data-new-window="true" target="_b
 lank" rel="noopener noreferrer">thesis</a> Advances in Computational 
 Art Connoisseurship
END:VEVENT
END:VCALENDAR
