Skip to main content
Have a personal or library account? Click to login
Data Mining Approach to Image Feature Extraction in Old Painting Restoration Cover

Data Mining Approach to Image Feature Extraction in Old Painting Restoration

Foundations of Computing and Decision Sciences
Volume 38 (2013): Issue 3 (September 2013)
By:  and    
Open Access
|Sep 2013
References

References

  1. [1] Abas F.S. (2004) Analysis of Craquelure Patterns for Content-Based Retrieval. PhD Thesis, University of Southampton, Southampton
    Search in Google Scholar
  2. [2] Abas F.S., Martinez K. (2003) Classi_cation of painting cracks for content-based analysis. IST/SPIE's 15th Annual Symp Electronic Imaging, Santa Clara, California, USA
    Open DOISearch in Google Scholar
  3. [3] Abas F.S., Martinez K. (2002) Craquelure analysis for content-based retrieval. Proc of 14th Int Conf on Dig Sig Proc, Santorini, Greece, 111{114
    Search in Google Scholar
  4. [4] Addis M., Lewis P., Martinez K. (2002) ARTISTE image retrieval system puts European galleries in the picture, Cultivate Interactive,7, http://www.cultivateint. org/issue7/artiste
    Search in Google Scholar
  5. [5] Barni M., Bartolini F., Cappellini V. (2000) Image processing for virtual restoration of artworks. IEEE Multimedia, 7,2:34{37
    Open DOISearch in Google Scholar
  6. [6] Barni M., Pelagotti A., Piva A. (2005) Image processing for the analysis and conservation of paintings: opportunities and challenges, IEEE Sig Proc Mag, 141
    Open DOISearch in Google Scholar
  7. [7] Berns R. S., Byrns S., Casadio F., Fiedler I., Gallagher C., Imai F. H., Newman A., Taplin L. A. (2006) Rejuvenating the color palette of George Seurats A Sunday on La Grande Jatte1884: A simulation. Color Research and Application 31:278293
    Search in Google Scholar
  8. [8] Berezhnoy I., Postma E. O., van den Herik H. J. (2007) Computer analysis of van goghs coplementary colours. Pattern Recognition Letters, 28:703709
    Open DOISearch in Google Scholar
  9. [9] Beucher S., Lantujoul C. (1979) Use of watersheds in contour detection. Proc. Int workshop on im proc, real-time edge and motion detection
    Search in Google Scholar
  10. [10] Bucklow S.L. (1998) A sylometric analysis of Craquelure. Computers and the Humanities 31:503{521
    Search in Google Scholar
  11. [11] Canny J. (1986) A Computational Approach To Edge Detection, IEEE Trans. Pattern Analysis and Machine Intelligence, 8:679-714
    Open DOISearch in Google Scholar
  12. [12] Cappellini V., Barni M., Corsini M., de Rosa A., Piva A. (2003) ArtShop: an art-oriented image-processing tool for cultural heritage applications. J Visual Comput Animat 14:149-158
    Open DOISearch in Google Scholar
  13. [13] Cappellini V., Piva A. (2006) Opportunities and Issues of image processing for cultural heritage applications, Proc EUSIPCO 2006, Florence, Italy
    Search in Google Scholar
  14. [14] Dik J., Janssens K., Van Der Snickt G., van der Loe_ L., Rickers K., Cotte M. (2008) Visualization of a lost painting by Vincent van Gogh using synchrotron radiation based X-ray uorescence elemental mapping. Analytical Chemistry, 80(16):64366442
    Search in Google Scholar
  15. [15] Fox M.D., Frizzell L.A., Franks L.A., Darken L.S., James R.B. (2000) Medical Imaging. The Electrical Engineering Handbook (ed. Dorf R.C.), CRC Press LLC, Boca Raton
    Search in Google Scholar
  16. [16] Gonzalez R.C., Woods R. (2007) Digital Image Processing, 3rd Edition, Prentice Hall
    Search in Google Scholar
  17. [17] Gupta A., Khandelwal V., Gupta A., Srivastava M.C. (2008) Image processing methods for the restoration of digitized paintings. Thammasat Int J Sc Tech 13,3:66{72
    Search in Google Scholar
  18. [18] Hanbury A., Kammerer P., Zolda E. (2003) Painting crack elimination using viscous morphological reconstruction. Proc ICIAP'03 Mantova, Italy
    Search in Google Scholar
  19. [19] Heckerman D., Geiger D., Chickering D. M. (1995) Learning Bayesian networks: The combination of knowledge and statistical data, Machine Learning 20(3), pp. 197-243, DOI:10.1007/BF00994016
    Open DOISearch in Google Scholar
  20. [20] Jacobsen C.R. (2012) Digital Painting Analysis. Authentication and Artistic Style from Digital Reproductions. PhD thesis, Department of Mathematical Sciences, Aalborg University, Aalborg
    Search in Google Scholar
  21. [21] Johnson C. R. Jr., Hendriks E., Berezhnoy I., Brevdo E., Hughes S. M., Daubechies I., Li J., Postma E., Wang J. Z. (2008) Image processing for artist identi_cation. IEEE Signal Processing Magazine (39)
    Open DOISearch in Google Scholar
  22. [22] Johnson C.R., Hendriks E. (2007) Brushwork in the Paintings of Vincent Van Gogh, Proc. 1st IP4AI Workshop, May 2007, Amsterdam, the Netherlands
    Search in Google Scholar
  23. [23] Lettner M., Sablatnig R. (2009) Spatial and spectral based segmentation of text in multispectral images of ancient documents. Proc. 10th International Conference on Document Analysis and Recognition (ICDAR 2009), pp. 813817, Barcelona, Spain
    Open DOISearch in Google Scholar
  24. [24] Lettner M., Diem M., Sablatnig R., Miklas H. (2008) Registration and enhancing of multispectral manuscript images. Proc. EUSIPCO08, Lausanne, Switzerland
    Search in Google Scholar
  25. [25] Liu J., Lu D. (2008) Knowledge based lacunas detection and segmentation for ancient paintings, Proc. of the 13th Int. Conf. on Virtual Systems and Multimedia, 121{131
    Search in Google Scholar
  26. [26] Lizun D. Fine Art Conservation, http://_neartconservation.ie/damian-lizun-_ne-art-conservation-4-4-43.html
    Search in Google Scholar
  27. [27] Martinez K., Goodal S. (2008) Colour cluster analysis for pigment identi_cation. Proc. SPIE Electronic Imaging: Computer Image Analysis in the Study of Art, San Jose, USA
    Open DOISearch in Google Scholar
  28. [28] MSDN: Microsoft Clustering Algorithm Technical Reference, http://msdn.microsoft.com/en-us/library/cc280445 (2013)
    Search in Google Scholar
  29. [29] MSDN: Microsoft Decision Trees Algorithm Technical Reference, http://msdn.microsoft.com/en-us/library/cc645868 (2013)
    Search in Google Scholar
  30. [30] Pappas M., Pitas I. (2000) Digital Color Restoration of Old Paintings, IEEE Transactions on Image Processing, 9(2), pp.291-294
    Search in Google Scholar
  31. [31] Renna F., Mosca N., Carlomagno G., Attolico G., Distante A. (2005) An innovative aided virtual aproach to the recomposition of fragments. Proc. 22nd International Symposium on Automation and Robotics in Construction, pp. 16, Ferrara, Italy
    Open DOISearch in Google Scholar
  32. [32] Serra J. (1982) Image Analysis and Mathematical Morphology Vol.I, Ac. Press, London
    Search in Google Scholar
  33. [33] Shahram M., Stork D. G., Donoho D. (2008) Recovering layers of brush strokes through statistical analysis of color and shape: an application to van goghs self portrait with grey felt hat. Comp. Im. Analysis in the Study of Art (6810)
    Open DOISearch in Google Scholar
  34. [34] Sobczyk J. (2008), Computer Image Analysis as a Method to Calculate the Original Surface Area of the Banner, in: Ivan Mazepas Hetmans Banner (Conservation Work at the National Museum in Krakow), pp. 216{217, Krakow
    Search in Google Scholar
  35. [35] Sobczyk J., Obara B., Fraczek P., Sobczyk J. (2006) The application of image analysis in non-invasive research of historical objects. Selected examples. [in Polish: Zastosowania analizy obrazu w nieniszczacych badaniach obiektow zabytkowych. Wybrane przyklady], Ochrona zabytkow, 2:69{78
    Search in Google Scholar
  36. [36] Stanco F., Battiato S., Gallo G. (2011) Digital Imaging for Cultural Heritage Preservation: Analysis, Restoration, and Reconstruction of Ancient Artworks. CRC Press
    Search in Google Scholar
  37. [37] Stergiopoulos S. (ed.) (2000) Advanced Signal Processing Handbook: Theory and Implementation for Radar, Sonar, and Medical Imaging Real-Time Systems. CRC Press LLC, Boca Raton, Florida
    Open DOISearch in Google Scholar
  38. [38] Stork D.G. (2004) Optics and realism in Renaissance art. Scienti_c American 291,6:76{83
    Open DOISearch in Google Scholar
  39. [39] Stork D.G. (2009) Computer vision and computer graphics analysis of paintings and drawings: An introduction to the literature. Proc 13th Int Conf on Computer Analysis of Images and Patterns, 9{24
    Open DOISearch in Google Scholar
  40. [40] Stout G.L. (1977) A trial index of laminal disruption. JAIC 17,1,3:17{26
    Open DOISearch in Google Scholar
  41. [41] Szabo T.L. (2004) Diagnostic Ultrasound Imaging: Inside Out. Academic Press series in Biomedical Engineering, Elsevier Academic Press
    Search in Google Scholar
  42. [42] Szeliski R. (2011) Computer Vision. Algorithms and Applications. Springer- Verlag, London
    Open DOISearch in Google Scholar
  43. [43] Tadeusiewicz R., Korohoda P. (1997) Computer Analysis and Image Processing [in Polish: Komputerowa analiza i przetwarzanie obrazow], Progress of Telecommunication Foundation Publishing House, Krakow
    Search in Google Scholar
  44. [44] Toler-Franklin C., Brown B., Weyrich T., Funkhouser T. Rusinkiewicz S. (2010) Multi-feature matching of fresco fragments. ACM Transactions on Graphics (TOG) - Proc. ACM SIGGRAPH Asia 29(6)
    Open DOISearch in Google Scholar
  45. [45] Ünsalan C., Boyer K.L. (2011) Multispectral Satellite Image Understanding. From Land Classi_cation to Building and Road Detection, Springer-Verlag London, London
    Open DOISearch in Google Scholar
  46. [46] De Willigen P. (1999) A Mathematical Study on Craquelure and other Mechanical Damage in Paintings. Delft University Press, Delft
    Search in Google Scholar
DOI: https://doi.org/10.2478/fcds-2013-0007 | Journal eISSN: 2300-3405 (formerly 0867-6356) | Journal ISSN: 0867-6356
Journal RSS Feed
Language: English
Page range: 159 - 174
Published on: Sep 27, 2013
Published by: Poznan University of Technology
In partnership with: Paradigm Publishing Services
Keywords:
data mining application,
image processing,
k-means clustering,
decision tree based image segmentation,
virtual restoration of paintings
Related subjects:
Computer sciences,
Software development

© 2013 Joanna Gancarczyk, Joanna Sobczyk, published by Poznan University of Technology
This work is licensed under the Creative Commons License.

Volume 38 (2013): Issue 3 (September 2013)
Previous article
Next article