Digital Support for Archaeology

Abstract We describe an interdisciplinary approach in which computer scientists develop techniques to support archaeology. In the Reading Images for the Cultural Heritage (RICH) project, a variety of methods have been developed to support archaeologists in the visualization, categorization, and characterization of archaeological objects, such as medieval glass, coins, ceramics, and seeds. The methods are based on image processing and machine learning algorithms that are tailored to the task at hand. We describe the algorithms and illustrate their application on archaeological datasets. The virtues and pitfalls of the interdisciplinary approach to archaeology are discussed.

[1]  E. W. Adams,et al.  Archaeological Typology and Practical Reality: A Dialectical Approach to Artifact Classification and Sorting , 1991 .

[2]  Guojun Lu,et al.  Evaluation of MPEG-7 shape descriptors against other shape descriptors , 2003, Multimedia Systems.

[3]  Heng Tao Shen,et al.  Dimensionality Reduction , 2009, Encyclopedia of Database Systems.

[4]  Dong-Gyu Sim,et al.  A modified Zernike moment shape descriptor invariant to translation, rotation and scale for similarity-based image retrieval , 2000, 2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532).

[5]  Geoffrey E. Hinton,et al.  Visualizing Data using t-SNE , 2008 .

[6]  W. Torgerson.  Multidimensional scaling: I. Theory and method , 1952 .

[7]  Shree K. Nayar,et al.  Reflectance and texture of real-world surfaces , 1999, TOGS.

[8]  R. Dunnell.  Archaeological Typology and Practical Reality: A Dialectical Approach to Artifact Classification and Sorting , 1993, American Antiquity.

[9]  Eric O. Postma,et al.  Dimensionality Reduction: A Comparative Review , 2008 .

[10]  Josef Kittler,et al.  Efficient and Robust Retrieval by Shape Content through Curvature Scale Space , 1998, Image Databases and Multi-Media Search.

[11]  Jitendra Malik,et al.  Shape matching and object recognition using shape contexts , 2010, 2010 3rd International Conference on Computer Science and Information Technology.

[12]  Nicolai Petkov,et al.  Distance sets for shape filters and shape recognition , 2003, IEEE Trans. Image Process..

[13]  John W. Sammon,et al.  A Nonlinear Mapping for Data Structure Analysis , 1969, IEEE Transactions on Computers.

[14]  Atilla Baskurt,et al.  Generalizations of angular radial transform for 2D and 3D shape retrieval , 2005, Pattern Recognit. Lett..

[15]  Hans Burkhardt,et al.  A Fast and Reliable Coin Recognition System , 2007, DAGM-Symposium.