Developing Mathematical Tools to Investigate Art
Inhaltsverzeichnis
Reference
Ingrid Daubechies: Developing Mathematical Tools to Investigate Art. In: Bridges 2012. Pages 9–16
DOI
Abstract
This paper tells the history of a project investigating authenticity and forgery in Van Gogh paintings using mathe- matical tools based on wavelet transformations.
Extended Abstract
Bibtex
Used References
[1] N. G. Kingsbury, “Complex wavelets for shift invariant analysis and filtering of signals”, Applied and Computational Harmonic Analysis, 10, no 3, May 2001, pp. 234-253.
[2] I. W. Selesnick, “A new complex-directional wavelet transform and its application to image denoising”, Proc. International Conference of Image Processing (ICIP) 2002, Vol. III, pp. 573-576.
[3] H. Choi, J. Romberg, R. Baraniuk and N. G. Kingsbury, “Hidden Markov tree modelling of com- plex wavelet transforms”, Proc. International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2000, Istanbul (Turkey).
[4] E.O. Postma, H.J. van den Herik and J.C.A. van der Lubbe, “Paintings and writings in the hands of scientists”, Pattern Recognition Letters, 28 (2007) pp. 671-672.
[5] S. Jafarpour, G. Polatkan, E. Brevdo, S. Hughes, A. Brasoveanu, and I. Daubechies, Stylistic Analysis of Paintings Using Wavelets and Machine Learning, European Signal Processing Conference (EUSIPCO), 2009.
[6] C.R. Johnson, E. Hendriks, I.J. Berezhnoy, E. Brevdo, S.M. Hughes, I. Daubechies, J. Li, E.O. Postma and J. Wang, (2008). “Image Processing for Artist Identification.” IEEE Signal Processing Magazine, 25 (2008), pp. 37-48.
[7] S. Jafarpour, G. Polatkan, E. Brevdo, S. Hughes, A. Brasoveanu, and I. Daubechies, “Stylistic Analysis of Paintings Using Wavelets and Machine Learning”, European Signal Processing Conference (EU- SIPCO), 2009.
Links
Full Text
http://archive.bridgesmathart.org/2012/bridges2012-9.pdf
