MOSAIC: Multi-object Segmentation for Assisted Image ReConstruction

  • Sonia Caggiano
  • Maria De MarsicoEmail author
  • Riccardo Distasi
  • Daniel Riccio
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9493)


This paper presents a tool targeted at archaeologists and cultural heritage operators. The tool assists the process of reconstructing broken pictorial artifacts from their physical fragments. The fragments are organized into a database indexed on features such as color distribution, shape and texture. The system can be queried using any fragment as the key, and the results are displayed from the most similar to the most dissimilar. The system provides the operator with complete workflow from photoacquisition onwards. The performance has been assessed with computer simulations and a real use case. Two of the simulations are discussed, as well as the real use case, based on an actual XV century fresco that needed reconstruction.


Image processing Feature extraction Feature-based indexing Jigsaw puzzle Cultural heritage 


  1. 1.
    Birchfield, S.T., Rangarajan, S.: Spatiograms versus histograms for region-based tracking. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 1158–1163, Jun 2005Google Scholar
  2. 2.
    Brown, B., Laken, L., Dutré, P., Gool, L.V., Rusinkiewicz, S., Weyrich, T.: Tools for virtual reassembly of fresco fragments. In: Proceedings of the 7th International Conference on Science and Technology in Archaeology and Conservations. pp. 1–10. SCITEPRESS (2010)Google Scholar
  3. 3.
    Brown, B., Toler-Franklin, C., Nehab, D., Burns, M., Dobkin, D., Vlachopoulos, A., Doumas, C., Rusinkiewicz, S., Weyrich, T.: A system for high-volume acquisition and matching of fresco fragments: reassembling theran wall paintings. ACM Trans. Graph. (Proc. SIGGRAPH) 27(3), 1–10 (2008)CrossRefGoogle Scholar
  4. 4.
    Cho, T.S., Avidan, S., Freeman, W. T.: A probabilistic image jigsaw puzzle solver. In: CVPR, pp. 183–190. IEEE (2010).
  5. 5.
    Chung, M.G., Fleck, M., Forsyth, D.: Jigsaw puzzle solver using shape and color. In: Proceedings of the 4th International Conference on Signal Processing (ICSP 1998). vol. 2, pp. 877–880 (1998)Google Scholar
  6. 6.
    Comaniciu, D., Meyer, P.: Mean shift: a robust approach toward feature space analysis. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 24(5), 603–619 (2002)CrossRefGoogle Scholar
  7. 7.
    Demaine, E.D., Demaine, M.L.: Jigsaw puzzles, edge matching, and polyomino packing: connections and complexity. Graphs Combinatorics 23(Supplement), 195–208 (2007). (special issue on Computational Geometry and Graph Theory: The Akiyama-Chvatal Festschrift)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Freeman, H., Garder, L.: Apictorial jigsaw puzzles: the computer solution of a problem in pattern recognition. IEEE Trans. Electron. Comput. 2(EC–13), 118–127 (1964)CrossRefGoogle Scholar
  9. 9.
    Hu, M.: Visual pattern recognition by moment invariants. IRE Trans. Inf. Theor. IT–8, 179–187 (1962)zbMATHGoogle Scholar
  10. 10.
    Mercimek, M., Mumcu, K.G.T.V.: Real object recognition using moment invariants. Sadhana Acad. Proc. Eng. Sci. 30(6), 765–775 (2005)zbMATHGoogle Scholar
  11. 11.
    Nielsen, T.R., Drewsen, P., Hansen, K.: Solving jigsaw puzzles using image features. Pattern Recogn. Lett. 14(29), 1924–1933 (2008)CrossRefGoogle Scholar
  12. 12.
    Papaodysseus, C., Panagopoulos, T., Exarhos, M.: Contour-shape based reconstruction of fragmented, 1600 bc wall paintings. IEEE Trans. Signal Process. 6(50), 1277–1288 (2002)CrossRefGoogle Scholar
  13. 13.
    Sagiroglu, M., Ercil, A.: A texture based matching approach for automated assembly of puzzles. In: Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006). pp. 1036–1041 (2006)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Sonia Caggiano
    • 1
  • Maria De Marsico
    • 2
    Email author
  • Riccardo Distasi
    • 3
  • Daniel Riccio
    • 4
  1. 1.Master of Architecture and PhD in Digital Painting RestorationSalernoItaly
  2. 2.Sapienza University of RomeRomeItaly
  3. 3.University of SalernoFiscianoItaly
  4. 4.University of Naples “Federico II”Campi FlegreiItaly

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