@article{efaf23393a884f6694cbf0ab3cdebae8,
title = "Image processing for artist identification: Computerized analysis of Vincent van Gogh's painting brushstrokes",
abstract = "A description on the approaches to brushwork analysis and artist identification within the framework of data set is given. Image processing is now a reality in painting analysis as high resolution and richer data are also available. A summary on the results that are obtained by several groups are presented who uses wavelet decomposition of the same data set. Better results can easily be achieved with the use of wider range of signal analysis tools. Furthermore, there is a growth within interested researchers, targeted conference sessions, and specialist workshops regarding painting analysis.",
author = "Johnson, {C. Richard} and Ella Hendriks and Berezhnoy, {Igor J.} and Eugene Brevdo and Hughes, {Shannon M.} and Ingrid Daubechies and Jia Li and Eric Postma and Wang, {James Z.}",
note = "Funding Information: Eugene Brevdo (
[email protected]) is a graduate student in electrical engineering at Princeton University. His research interests include signal processing and machine learning, with applications to computer vision and inverse problems in medical imaging. His work is supported by the NDSEG and Gordon Wu fellowships. Funding Information: The authors thank the Van Gogh and Kr{\"o}ller-M{\"u}ller Museums for granting access to such a rich data set and for their continuing support of this cross-disciplinary interaction. They acknowledge the constructive comments of the anonymous reviewers. J. Li and J. Wang would like to thank their former student Weina Ge for assistance in implementing the geometric analysis and conducting the related experiments. National Science Foundation Grants IIS0347148 and EIA0202007 provided partial funding for their research. S.M. Hughes and E. Brevdo thank Peter Ramadge for many interesting discussions and suggestions. I. Daubechies gratefully acknowledges partial support of NSF grants DMS0245566 and DMS0354464. The research of I. Berezhnoy and E. Postma was carried out within the Netherlands Organization for Scientific Research (NWO) ToKeN project Authentic (grant 634.000.015). C.R. Johnson, Jr. was supported in part by a Fulbright Fellowship (2005) and a Stephen H. Weiss Presidential Fellowship (2005–2009). Funding Information: Shannon M. Hughes (
[email protected]) is a Ph.D. student in electrical engineering at Princeton University. Her thesis research focuses on the development of mathematical methods for the analysis of complex data, with applications to problems in both neuroscience and art history. She has received an NSF Graduate Fellowship, a Princeton University Gordon S. Wu Fellowship, and an NIH Ruth L. Kirchstein National Research Service Award.",
year = "2008",
month = jul,
doi = "10.1109/MSP.2008.923513",
language = "English (US)",
volume = "25",
pages = "37--48",
journal = "IEEE Signal Processing Magazine",
issn = "1053-5888",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "4",
}