Recognising Familiar Facial Features in Paintings Belonging to Separate Domains

  • Wilbert TaboneEmail author
  • Dylan Seychell
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9256)


We present a system\(^1\) that detects faces in various paintings and subsequently recognise and points out any similarities that a certain face in one painting may have to another on a different artwork. The results would be ranked up according to similarity in a bid to produce an output that may assist art researchers to discover new links between different works which pertain to the same or different artist. Through various tests conducted, we have proved that our method was successful in exposing new links of similarity in various scenarios including cases where the human visual system failed to pinpoint any.


Linear Discriminant Analysis Human Visual System Face Detection Query Image Histogram Equalisation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Aleksander, I., De Gregorio, M., França, F.M.G., Lima, P.M.V., Morton, H.: A brief introduction to weightless neural systems. In: ESANN. Citeseer (2009)Google Scholar
  2. 2.
    Aleksander, I., Morton, H.: An introduction to neural computing, vol. 3. Chapman & Hall, London (1990) Google Scholar
  3. 3.
    Beham, M.P., Roomi, S.M.M.: Face recognition using appearance based approach: a literature survey. In: Proceedings of International Conference & Workshop on Recent Trends in Technology, Mumbai, Maharashtra, India, pp. 24–25 (2012)Google Scholar
  4. 4.
    Canny, J.: A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 6, 679–698 (1986)CrossRefGoogle Scholar
  5. 5.
    Johnson, M.: A brief introduction to kernel classifiers (2009)Google Scholar
  6. 6.
    Maini, R., Aggarwal, H.: Study and comparison of various image edge detection techniques. International Journal of Image Processing (IJIP) 3(1), 1–11 (2009)Google Scholar
  7. 7.
    Medioni, G., Kang, S.B.: Emerging topics in computer vision. Prentice Hall PTR (2004)Google Scholar
  8. 8.
    Nilsson, M.: Face detection. Presentation by the Mathematical Imaging Group, Centre for Math ematical Sciences, Lund University (2014)Google Scholar
  9. 9.
    Nixon, M.: Feature extraction & image processing. Academic Press (2008)Google Scholar
  10. 10.
    Pereira, F., Mitchell, T., Botvinick, M.: Machine learning classifiers and fmri: a tutorial overview. Neuroimage 45(1), S199–S209 (2009)CrossRefGoogle Scholar
  11. 11.
    Pressman, R.S.: Software engineering: a practitioners approach. McGrow-Hill International Edition (2005)Google Scholar
  12. 12.
    Rabbani, M., Chellappan, C.: A different approach to appearance-based statistical method for face recognition using median. International Journal of Computer Science and Network Security 7(4), 262–267 (2007)Google Scholar
  13. 13.
    Fisher, R., Perkins, S., Walker, A., Wolfart, E.: Sobel edge detector. HPR2 (2004)Google Scholar
  14. 14.
    Saleh, B., Abe, K., Arora, R.S., Elgammal, A.M.: Toward automated discovery of artistic influence (2014). CoRR abs/1408.3218Google Scholar
  15. 15.
    Sciberras, K.: Francesco Zahra: His life and art in mid-18th century Malta 1710–1773. Midsea Books (2010)Google Scholar
  16. 16.
    Shrivakshan, G., Chandrasekar, C.: A comparison of various edge detection techniques used in image processing. IJCSI International Journal of Computer Science Issues 9(5), 269–276 (2012)Google Scholar
  17. 17.
    Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, vol. 1, pp. I-511. IEEE (2001)Google Scholar
  18. 18.
    Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing 13(4), 600–612 (2004)CrossRefGoogle Scholar
  19. 19.
    Yang, M.H., Ahuja, N.: Face detection and gesture recognition for human-computer interaction, vol. 1. Springer (2001)Google Scholar
  20. 20.
    Yang, M.H., Kriegman, D., Ahuja, N.: Detecting faces in images: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(1), 34–58 (2002)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.St. Martin’s Institute of Higher EducationHamrun Malta

Personalised recommendations