Review of computer-based methods for archaeological ceramic sherds reconstruction
Potteries are the most numerous finds found in archaeological excavations; they are often used to get information about the history, economy, and art of a site. Archaeologists rarely find complete vases but, generally, damaged and in fragments, often mixed with other pottery groups. By using the traditional manual method, the analysis and reconstruction of sherds are performed by a skilled operator. Reviewed papers provided evidence that the traditional method is not reproducible, not repeatable, time-consuming and its results have great uncertainties. To overcome the aforementioned limits, in the last years, researchers have made efforts to develop computer-based methods for archaeological ceramic sherds analysis, aimed at their reconstruction. To contribute to this field of study, in this paper, a comprehensive analysis of the most important available publications until the end of 2019 is presented. This study, focused on pottery fragments only, is performed by collecting papers in English by the Scopus database using the following keywords: “computer methods in archaeology", "3D archaeology", "3D reconstruction", "automatic feature recognition and reconstruction", "restoration of pottery shape relics”. The list is completed by additional references found through the reading of selected papers. The 53 selected papers are divided into three periods of time. According to a detailed review of the performed studies, the key elements of each analyzed method are listed based on data acquisition tools, features extracted, classification processes, and matching techniques. Finally, to overcome the actual gaps some recommendations for future researches are proposed.
The traditional manual method for reassembling sherds is very time-consuming and costly; it also requires a great deal effort from skilled archaeologists in repetitive and routine activities.
Computer-based methods for archaeological ceramic sherds reconstruction can help archaeologists in the above-mentioned repetitive and routine activities.
In this paper, the state-of-the-art computer-based methods for archaeological ceramic sherds reconstruction are reviewed, and some recommendations for future researches are proposed.
Andrews, S., & Laidlaw, D. H. (2002). Toward a framework for assembling broken pottery vessels. In Proceedings of the National Conference on Artificial Intelligence, (August 2003), (pp. 945–946).
Banterle, F., Itkin, B., Dellepiane, M., Wolf, L., Callieri, M., Dershowitz, N., & Scopigno, R. (2017). VASESKETCH: Automatic 3D Representation of Pottery from Paper Catalog Drawings. In Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, 1(693548), (pp. 683–690). https://doi.org/10.1109/ICDAR.2017.117
Belenguer, C. S., & Vidal, E. V. (2012). Archaeological fragment characterization and 3D reconstruction based on projective GPU depth maps. In Proceedings of the 2012 18th International Conference on Virtual Systems & Multimedia, VSMM 2012: Virtual Systems in the Information Society, (pp. 275–282). https://doi.org/10.1109/VSMM.2012.6365935
Blender. (2018). An open-source 3D graphics and animation software. Retrieved from https://www.blender.org
Brown, B. J., Toler-Franklin, C., Nehab, D., Burns, M., Dobkin, D., Vlachopoulos, A., Weyrich, T. (2008). A system for high-volume acquisition and matching of fresco fragments: Reassembling Theran wall paintings. ACM Transactions on Graphics, 27(3). https://doi.org/10.1145/1360612.1360683
Cao, Y., & Mumford, D. (2002). Geometric Structure Estimation of Axially Symmetric Pots from Small Fragments. In Proceedings of the signal processing, pattern recognition and applications, IASTED, Crete, Greece, June 25–28, 2002, (pp. 92–97).
Cohen, F., Zhang, Z., & Jeppson, P. (2010). Virtual reconstruction of archaeological vessels using convex hulls of surface markings. 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition-Workshops, (pp. 55–61). http://dx.doi.org/10.1109/CVPRW.2010.5543528
Cohen, F., Zhang, Z., & Liu, Z. (2016). Mending broken vessels a fusion between color markings and anchor points on surface breaks. Multimedia Tools and Applications, 75(7), 3709–3732. https://doi.org/10.1007/s11042-014-2190-0
Cooper, D. B., Willis, A., Andrews, S., Baker, J., Cao, Y., Han, D., … others. (2001). Assembling virtual pots from 3D measurements of their fragments. In Proceedings of the 2001 Conference on Virtual Reality, Archeology, and Cultural Heritage, (pp. 241–254). https://doi.org/10.1145/584993.585032
Di Angelo, L., Di Stefano, P., Morabito, A. E., & Pane, C. (2018). Measurement of constant radius geometric features in archaeological pottery. Measurement: Journal of the International Measurement Confederation, 124 (March), 138–146. https://doi.org/10.1016/j.measurement.2018.04.016
Di Angelo, L., Di Stefano, P., & Pane, C. (2018). An automatic method for pottery fragments analysis. Measurement: Journal of the International Measurement Confederation, 128, 138–148. https://doi.org/10.1016/j.measurement.2018.06.008
Di Angelo, Luca, Di Stefano, P., & Pane, C. (2017). Automatic dimensional characterization of pottery. Journal of Cultural Heritage, 26, 118–128. https://doi.org/10.1016/j.culher.2017.02.003
Fragkos, S., Tzimtzimis, E., Tzetzis, D., Dodun, O., & Kyratsis, P. (2018). 3D laser scanning and digital restoration of an archaeological find. MATEC Web of Conferences, 178. https://doi.org/10.1051/matecconf/201817803013
Funkhouser, T., Shin, H., Toler-Franklin, C., Castañeda, A. G., Brown, B., Dobkin, D., Weyrich, T. (2011). Learning how to match fresco fragments. Journal on Computing and Cultural Heritage, 4(2). https://doi.org/10.1145/2037820.2037824
Halir, R., & Menard, C. (1996). Diameter estimation for archaeological pottery using active vision. In Proceedings of the 20th Workshop of the Austrian Association for Pattern Recognition (OAGM/AAPR) on Pattern Recognition 1996, (pp. 251–261).
Halir, R., & Flusser, J. (1997). Estimation of profiles of sherds of archaeological pottery. In Proceedings of the of the Czech Pattern Recognition Workshop (CPRW’97), Czech Republic, February 1997, 1–5, (pp. 126–130).
Halir, R. (1999). An Automatic Estimation Of The Axis Of Rotation Of Fragments Of Archaeological Pottery: A Multi-Step Model-Based Approach. In Proceedings of the 7th International Conference in Central Europe on Computer Graphics, Visualization and Interactive Digital Media (WSCG ’99) https://semanticscholar.org/0248/ae5a8dca3d2c6bfff282ce481a5625d32362
Hall, N. S., & Laflin, S. (1984). A computer aided design technique for pottery profiles. In Computer applications in Archaeology, (pp. 178-188). Computer Center, University of Birmingham Birmingham. Retrieved from https://www.bcin.ca/bcin/detail.app?id=40524
Han, D., & Hahn, H. S. (2014). Axis estimation and grouping of rotationally symmetric object segments. Pattern Recognition, 47(1), 296–312. https://doi.org/10.1016/j.patcog.2013.06.022
Hlavackova-Schindler, K., Kampel, M., & Sablatnig, R. (2001). Fitting of a Closed Planar Curve Representing a Profile of an Archaeological Fragment. In Proceedings VAST 2001 Virtual Reality, Archeology, and Cultural Heritage, (pp. 263–269). https://doi.org/10.1145/585031.585034
Huang, Q. X., Flöry, S., Gelfand, N., Hofer, M., & Pottmann, H. (2006). Reassembling fractured objects by geometric matching. ACM SIGGRAPH 2006 Papers, SIGGRAPH ’06, (May), (pp. 569–578). https://doi.org/10.1145/1179352.1141925
Igwe, P. C., & Knopf, G. K. (2006). 3D object reconstruction using geometric computing. Geometric Modeling and Imaging New Trends, 9–14. https://doi.org/10.1109/GMAI.2006.1
Kalasarinis, I., & Koutsoudis, A. (2019). Assisting pottery restoration procedures with digital technologies. International Journal of Computational Methods in Heritage Science, 3(1), 20–32. https://doi.org/10.4018/ijcmhs.2019010102
Kampel, M., & Sablatnig, R. (2003). Profile-based Pottery Reconstruction. In IEEE Proceeding of Conference on Computer Vision and Pattern Recognition Workshops, Wisconsin, June, (pp. 1-6). https://doi.org/10.1109/CVPRW.2003.10007
Kampel, M, & Mara, H. (2005). Robust 3D reconstruction of archaeological pottery based on concentric circular rills. In Proceedings of the Sixth International. Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS’05), Montreux, Switzerland, (pp. 14-20). Retrieved from https://semanticscholar.org/43df/9b3c6fef5aa54964bdc4825a86cc4e9f4531
Kampel, M., & Sablatnig, R. (2003). An automated pottery archival and reconstruction system. Journal of Visualization and Computer Animation, 14(3), 111–120. https://doi.org/10.1002/vis.310
Kampel, M., & Sablatnig, R. (2004). 3D Puzzling of Archeological Fragments. In Proceedings of 9th Computer Vision Winter Workshop, (February), (pp. 31–40). Retrieved from https://cvl.tuwien.ac.at/wp-content/uploads/2014/12/cvww041
Karasik, A., & Smilansky, U. (2011). Computerized morphological classification of ceramics. Journal of Archaeological Science, 38(10), 2644–2657. https://doi.org/10.1016/j.jas.2011.05.023
Kashihara, K. (2012). Three-dimensional reconstruction of artifacts based on a hybrid genetic algorithm. In IEEE International Conference on Systems, Man and Cybernetics, (pp. 900–905). https://doi.org/10.1109/ICSMC.2012.6377842
Kashihara, K. (2017). An intelligent computer assistance system for artifact restoration based on genetic algorithms with plane image features. International Journal of Computational Intelligence and Applications, 16(3), 1–15. https://doi.org/10.1142/S1469026817500213
Kleber, F., & Sablatnig, R. (2009). A survey of techniques for document and archaeology artifact reconstruction. In Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, (March 2014), (pp. 1061–1065). https://doi.org/10.1109/ICDAR.2009.154
Kotoula, E. (2016). Semiautomatic fragments matching and virtual reconstruction: a case study on ceramics. International Journal of Conservation Science, 7(1), 71-86. Retrieved from http://eprints.lincoln.ac.uk/id/eprint/31035/
Lucena, M., Martínez-Carrillo, A. L., Fuertes, J. M., Javier Carrascosa Malagón, F., & Ruiz Rodríguez, A. (2016). Decision support system for classifying archaeological pottery profiles based on mathematical morphology. Multimedia Tools and Applications, 75(7), 3677–3691. https://doi.org/10.1007/s11042-014-2063-6
Maiza, C., & Gaildrat, V. (2005). Automatic classification of archaeological potsherds. In Proceedings of the 8th International Conference on Computer Graphics and Artificial Intelligence, Limoges, France, May 11–12, 2005, (pp. 135–147). https://semanticscholar.org/3c95/82c3e562b44e7d61dc0fd3487ea3dc977ff3
Mara, H., Kampel, M., & Sablatnig, R. (2002). Preprocessing of 3D-Data for Classification of Archaeological Fragments in an Automated System. In Proceedings of the 26th Workshop of the Austrian Association for Pattern Recognition, Vision with Non-Traditional Sensors, (ÖAGM/AAPR), Graz, Austria, 10–11 September 2002, (pp. 257-264). https://doi.org/10.1.1.15.748
Mara, H., & Sablatnig, R. (2006). The orientation of fragments of rotationally symmetrical 3D-shapes for archaeological documentation. In Proceedings - Third International Symposium on 3D Data Processing, Visualization, and Transmission, 3DPVT 2006, (June), (pp. 1064–1071). https://doi.org/10.1109/3DPVT.2006.105
Melero, F. J., Torres, J. C., & Leon, A. (2003). On the interactive 3d reconstruction of Iberian vessels. In 4th International Symposium on Virtual Reality, Archaeology, and Intelligent Cultural Heritage, VAST, 3, (pp. 71–78). http://dx.doi.org/10.2312/VAST/VAST03/071-078
Papaioannou, G., Karabassi, E. a., & Theoharis, T. (2000). Automatic Reconstruction of Archaeological Finds–A Graphics Approach. In International Conference on Computer Graphics and Artificial Intelligence, (March), (pp. 117–125). Retrieved from https://semanticscholar.org/6a3c/7ec8f544bbfb83174d868cd406eaaf40f438
Papaioannou, G., Karabassi, E. A., & Theoharis, T. (2002). Reconstruction of three-dimensional objects through the matching of their parts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(1), 114–124. https://doi.org/10.1109/34.982888
Pulli, K. (1999). Multiview registration for large data sets. In Proceedings of Second International Conference on 3D Digital Imaging and Modeling, Ottawa, ON, Canada, 4–8 December 1999, (pp. 160–168). http://doi.org/10.1109/IM.1999.805346
Rasheed, N. A., & Nordin, J. (2015a). A Survey of Computer Methods in Reconstruction of 3D Archaeological Pottery Objects. International Journal of Advanced Research, 3(3), 712–714. Retrieved from https://academia.edu.documents/45540231
Rasheed, N. A., & Nordin, M. J. (2014). A polynomial function in the automatic reconstruction of fragmented objects. Journal of Computer Science, 10(11), 2339–2348. https://doi.org/10.3844/jcssp.2014.2339.2348
Rasheed, N. A., & Nordin, M. J. (2015b). Archaeological fragments classification based on RGB color and texture features. Journal of Theoretical and Applied Information Technology, 76(3), 358–365. Retrieved from http://repository.uobabylon.edu.iq/papers/publication.aspx?pubid=6746
Rasheed, N. A., & Nordin, M. J. (2018). Classification and reconstruction algorithms for the archaeological fragments. Journal of King Saud University-Computer and Information Sciences. https://doi.org/10.1016/j.jksuci.2018.09.019
Rasheed, N. A., Nordin, M. J., Dakheel, A. H., Nados, W. L., & Maaroof, M. K. A. (2017). Classification archaeological fragments into groups. Research Journal of Applied Sciences, Engineering, and Technology, 14(9), 324–333. https://doi.org/10.19026/rjaset.14.5072
Sablatnig, R., & Menard, C. (1997). 3D Reconstruction of Archaeological Pottery using Profile Primitives. In Proceedings of I International Workshop on Synthetic-Natural Hybrid Coding and Three-Dimensional Imaging, (pp. 93-96).
Sablatnig, R., Menard, C., & Kropatseh, W. (1998). Classification of archaeological fragments using a description language. In Proceedings of European Signal Processing Conference, (Eusipco ’98), (pp. 1097-1100), 1998.
Sakpere, W. (2019). 3D Reconstruction of Archaeological Pottery from Its Point Cloud. In Proceedings of Iberian Conference on Pattern Recognition and Image Analysis, (pp. 125-136). https://doi.org/10.1007/978-3-030-31332-6_11
Shin, H., Doumas, C., Funkhouser, T., Rusinkiewicz, S., Steiglitz, K.,
Vlachopoulos, & Weyrich, T. (2010). Analyzing Fracture Patterns in Theran Wall Paintings. In Proceedings of the 11th International Symposium on Virtual Reality, Archaeology - VAST, (pp. 71-78). https://doi.org/10.2312/VAST/VAST10/071-078
Son, K., Almeida, E. B., & Cooper, D. B. (2013). Axially symmetric 3D pots configuration system using the axis of symmetry and break curve. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, (pp. 257–264). https://doi.org/10.1109/CVPR.2013.40
Stamatopoulos, M. I., & Anagnostopoulos, C.-N. (2016). 3D digital reassembling of archaeological ceramic pottery fragments based on their thickness profile. The Computing Research Repository (CoRR). Retrieved from https://arxiv.org/abs/1601.05824
Toler-Franklin, C., Funkhouser, T., Rusinkiewicz, S., Brown, B., & Weyrich, T. (2010). Multi-Feature Matching of Fresco Fragments. ACM Transactions on Graphics, 29(6), 1–12. https://doi.org/10.1145/1882261.1866207
Üçoluk, G., & Hakki Toroslu, I. (1999). Automatic reconstruction of broken 3-D surface objects. Computers and Graphics, 23(4), 573–582. https://doi.org/10.1016/S0097-8493(99)00075-8
Vendrell-Vidal, E., & Sánchez-Belenguer, C. (2014). A Discrete Approach for Pairwise Matching of Archaeological Fragments. Journal on Computing and Cultural Heritage, 7(3), 1–19. https://doi.org/10.1145/2597178
Willis, A., Orriols, X., & Cooper, D. B. (2003). Accurately Estimating Sherd 3D Surface Geometry with Application to Pot Reconstruction. In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, (16-22 June 2003), Madison, Wisconsin, USA (pp. 1–7). https://doi.org/10.1109/CVPRW.2003.10014
Willis, A. R., & Cooper, D. B. (2004). Bayesian assembly of 3D axially symmetric shapes from fragments. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1, (pp. 82–89). https://doi.org/10.1109/cvpr.2004.1315017
Zhou, Mingquam, Geng, G., Wu, Z., Zheng, X., Shui, W., Lu, K., & Gao, Y. (2007). A system for re-assembly of fragment objects and computer-aided restoration of cultural relics. Virtual Retrospect 2007, 3, 21–27. Retrieved from http://hal.univ-savoie.fr/ENIB/hal-01765241v1
Zhou, Mingquan, Geng, G., Wu, Z., & Shui, W. (2010). A Virtual Restoration System for Broken Pottery. In Proceedings of the CAA Conference 37th Computer applications and quantitative methods in archaeology, Williamsburg, VA, USA, 22–26 March 2009; (pp. 391–396). Retrieved from https://semanticscholar.org/87b5/aa5c7710806677abbedb4e43f6134e053041
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