Abstract
The continuously increasing art market activity and international art transactions lead the market for stolen and fraudulent art to extreme levels. According to US officials, art crime is the third-highest grossing criminal enterprise worldwide. As a result, art forensics is a rising research field dealing with the identification of stolen or looted art and their collection and repatriation. Photographs of artwork provide, in several cases, the only way to locate stolen and looted items. However, it is quite common these items to be damaged as a result of excavation and illegal movement. Digital processing of photographs of damaged artwork is therefore of high importance in art forensics. This processing emphasizes on “object restoration” and although techniques from the field of image restoration can be applied it is of high importance to take into account the semantics of the artwork scene and especially the structure of objects appeared therein. In this paper, we assess the application of face image restoration techniques, applied on damaged faces appearing in Byzantine icons, in an attempt to identify the actual icons. Several biometric measurements and facial features along with a set of rules related to the design of Byzantine faces are utilized for this purpose. Preliminary investigation, applied on 25 icons, shows promising results.
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References
Ahonen, T., Hadid, A., Pietikainen, M.: Face description with local binary patterns: Application to face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(12), 2037–2041 (2006)
Atwood, R.: Stealing History, Tomb Raiders, Smugglers and the Looting of the Ancient World. St. Martin’s Griffin, New York (2006)
Barni, M., Bartolini, F., Cappellini, V.: Image processing for virtual restoration of artworks. IEEE Multimedia 7, 34–37 (2000)
Blanz, V., Vetter, T.: Face recognition based on fitting 3D morphable model. IEEE Transactions on Pattern Analysis and Machine Intelligence 25, 1063–1074 (2003)
Bowman, B.A.: Transnational Crimes Against Culture: Looting at Archaeological Sites and the ‘‘Grey’’ Market in Antiquities. Journal of Contemporary Criminal Justice 24(3), 225–242 (2008)
Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active Appearance Models. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(6), 681–685 (2001)
Dalal, N., Triggs, B.: Histograms of Oriented Gradients for Human Detection. In: Proc. of the 2005 IEEE Conference on Computer Vision and Pattern Recognition, pp. 886–893 (2005)
Hadjisavvas, S.: The Destruction of the Archaeological Heritage of Cyprus. Trade in Illicit Antiquities: The Destruction of the World’s Archaeological Heritage, 133–139
Del Mastio, A., Cappellini, V., Caldelli, R., De Rosa, A., Piva, A.: Virtual restoration and protection of cultural heritage images. In: 15th International Conference on Digital Signal Processing, pp. 471–474 (2007)
Drago, F., Chiba, N.: Locally adaptive chromatic restoration of digitally acquired paintings. International Journal of Image and Graphics 5, 617–637 (2005)
Giakoumis, I., Nikolaidis, N., Pitas, I.: Digital image processing techniques for the detection and removal of cracks in digitized paintings. IEEE Transactions on Image Processing 15, 178–188 (2006)
Lanitis, A.: Person Identification From Heavily Occluded Face Images. In: Procs. of the ACM Symposium of Applied Computing, vol 1, pp. 5–9 (2004)
Lanitis, A., Stylianou, G., Voutounos, C.: Virtual restoration of faces appearing in Byzantine icons. International Journal of Cultural Heritage 13(4), 404–412(2012)
Lowe, D.G.: Distinctive image features from scale invariant keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)
Maronidis, A., Lanitis, A.: An Automated Methodology for Assessing the Damage on Byzantine Icons. In: Ioannides, M., Fritsch, D., Leissner, J., Davies, R., Remondino, F., Caffo, R. (eds.) EuroMed 2012. LNCS, vol. 7616, pp. 320–329. Springer, Heidelberg (2012)
Maronidis, A., Voutounos, C., Lanitis, A.: Designing and Evaluating an Expert System for Restoring Damaged Byzantine Icons. Multimedia Tools and Applications, 1-24 (2013)
National Academy of Sciences. Strengthening Forensic Science in the United States: A Path Forward. Doc. No. 228091, Washington, D.C. (2009)
Park, J.S., Oh, Y., Ahn, S., Lee, S.W.: Glasses removal from facial image using recursive PCA reconstruction. In: Kittler, J., Nixon, M.S. (eds.) AVBPA 2003. LNCS, vol. 2688. Springer, Heidelberg (2003)
Renfrew, C.: Loot, legitimacy and ownership: the ethical crisis in archaeology. Duckworth, London (2000)
Spagnolo, G.S, Somma, F.: Virtual restoration of cracks in digitized image of paintings. Journal of Physics Conference Series 249(1) (2010)
Theodosiou, Z. Tsapatsoulis, N.: Spatial Histogram of Keypoints. In: Proc. of the 20th IEEE Intl. Conference on Image Processing, pp. 2924–2928.
Vranos, I.C.: H Techniki tis Agiographias. P. S. Pournaras (In Greek), Thessaloniki (2001)
Wang, Z.M., Tao, J.H.: Reconstruction of partially occluded face by fast recursive PCA. In: International Conference on Computational Intelligence and Security Workshops, Harbin (December 15-19, 2007)
Wu, C., Liu, C., Shum, H.Y., Xy, Y.Q., Zhang, Z.: Automatic eyeglasses removal from face images. IEEE Transactions on Pattern Analysis and Machine Intelligence 26, 322–336 (2004)
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Lanitis, A., Tsapatsoulis, N., Maronidis, A. (2014). On the Application of Biometric Techniques for Locating Damaged Artworks. In: Cantoni, V., Dimov, D., Tistarelli, M. (eds) Biometric Authentication. BIOMET 2014. Lecture Notes in Computer Science(), vol 8897. Springer, Cham. https://doi.org/10.1007/978-3-319-13386-7_20
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DOI: https://doi.org/10.1007/978-3-319-13386-7_20
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