A Technique for Computerised Brushwork Analysis

Dmitry Murashov, Alexey Berezin, Ekaterina Ivanova

2015

Abstract

In this work, the problem of computer-assisted attribution of fine-art paintings based on image analysis methods is considered. A technique for comparing artistic styles is proposed. Textural features represented by histograms of brushstroke ridge orientation and local neighborhood orientation are used in this work to characterize painter's artistic style. The procedures for feature extraction are developed and the parameters are chosen. The paintings are compared using three informative fragments segmented in a particular image. Selected image fragments are compared by information-theoretical dissimilarity measure. The technique is tested on images of portraits created in 17-19th centuries. The preliminary results of the experiments showed that the difference between portraits painted by the same artist is substantially smaller than one between portraits painted by different authors. The proposed technique may be used as a part of technological description of fine art paintings for attribution. The unsolved problems are pointed out and the directions of further research are outlined.

References

  1. Obukhov, G., 1959. A brief glossary of fine art. Moscow, The soviet painter. (In Russian).
  2. Stone, D., Stork, D., 2010. Computer-assisted Connoisseurship: The Interdisciplinary Science of Computer Vision and Image Analysis in the Study of Art, IP4AI3, Museum of Modern Art, New York, May 27, pp. 9-10.
  3. Morelli, G., 1900. Italian Painters. Critical Studies of Their Works. John Murray, London.
  4. Berenson. B., 1903. The Study and Criticism of Italian Art. George Bell and sons, London.
  5. Ignatova, N, 1994. Analysis of oil painting textures. In Fundamentals of Oil painting Examination. The guidelines, Moscow, Grabar restoration Centre, vol. 1.
  6. Johnson, C. R., Hendriks, E., Berezhnoy, I.J., Brevdo, E., Hughes, S.M., Daubechies, I., Li, J., Postma, E., Wang, J.Z., 2008. Image processing for artist identification (Computerized analysis of Vincent van Gogh's painting brushstrokes). Signal Processing Magazine, IEEE. Vol. 25, No 4. - P. 37-48.
  7. Polatkan, G., Jafarpour, S., Brasoveanu, A., Hughes, S., Daubechies, I., 2009. Detection of forgery in paintings using supervised learning. ICIP2009, IEEE. P. 2921- 2924.
  8. Lettner, M., M. Sablatnig, M., 2005. Texture Analysis for Stroke Classification in Infrared Reflectogramms. H. Kalviainen et al. Eds., SCIA 2005, Springer-Verlag Berlin-Heidelberg, LNCS. Vol. 3540. - P. 459-469.
  9. Shahram, M., Stork, D.G., Donoho, D., 2008. Recovering layers of brush strokes through statistical analysis of color and shape: an application to van Gogh's Self portrait with grey felt hat. Computer Image Analysis in the Study of Art. D. Stork, J. Coddington, Eds.: Proc. of the SPIE. Vol. 6810. - P. 68100D-1 - 68100D-8.
  10. Li, J., Yao, L., Hendriks, E., Wang, J. Z., 2012. Rhythmic brushstrokes distinguish van Gogh from his contemporaries: findings via automated brushstroke extraction. IEEE TPAMI. Vol. 34, No 6. - P. 1159- 1176.
  11. Sablatnig, R., Kammerer, P., Zolda, E., 1998. Structural Analysis of Paintings Based on Brush Strokes. Proc. of SPIE Scientic Detection of Fakery in Art. SPIE. Vol.. 3315. - P. 87-98.
  12. Murashov, D., 2014. Localization of differences between multimodal images on the basis of an informationtheoretical measure, Pattern Recognition and Image Analysis. Springer, Vol. 24, No 1. - P. 133-143.
  13. Escolano, F., Suau, P., Bonev, B., 2009. Information Theory in Computer Vision and Pattern Recognition. - London, Springer Verlag.
  14. Eberly, D., 1996. Ridges in Image and Data Analysis. Klewer Academic Publishers.
  15. Lindeberg, T., 1994. Scale-space Theory in Computer Vision. Kluwer Academic Publishers.
  16. Jähne, B. 2005. Digital Image Processing. 6th ed. Springer.
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Paper Citation


in Harvard Style

Murashov D., Berezin A. and Ivanova E. (2015). A Technique for Computerised Brushwork Analysis . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-091-8, pages 221-226. DOI: 10.5220/0005362302210226


in Bibtex Style

@conference{visapp15,
author={Dmitry Murashov and Alexey Berezin and Ekaterina Ivanova},
title={A Technique for Computerised Brushwork Analysis},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={221-226},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005362302210226},
isbn={978-989-758-091-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)
TI - A Technique for Computerised Brushwork Analysis
SN - 978-989-758-091-8
AU - Murashov D.
AU - Berezin A.
AU - Ivanova E.
PY - 2015
SP - 221
EP - 226
DO - 10.5220/0005362302210226