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Automatic Classification of Decorative Patterns in the Minoan Pottery of Kamares Style

Automatic Classification of Decorative Patterns in the Minoan Pottery of Kamares Style

Filippo Stanco, Davide Tanasi, Giuseppe Claudio Guarnera, Giovanni Gallo
Copyright: © 2013 |Pages: 19
ISBN13: 9781466620384|ISBN10: 1466620382|EISBN13: 9781466620391
DOI: 10.4018/978-1-4666-2038-4.ch068
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MLA

Stanco, Filippo, et al. "Automatic Classification of Decorative Patterns in the Minoan Pottery of Kamares Style." Geographic Information Systems: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2013, pp. 1132-1150. https://doi.org/10.4018/978-1-4666-2038-4.ch068

APA

Stanco, F., Tanasi, D., Guarnera, G. C., & Gallo, G. (2013). Automatic Classification of Decorative Patterns in the Minoan Pottery of Kamares Style. In I. Management Association (Ed.), Geographic Information Systems: Concepts, Methodologies, Tools, and Applications (pp. 1132-1150). IGI Global. https://doi.org/10.4018/978-1-4666-2038-4.ch068

Chicago

Stanco, Filippo, et al. "Automatic Classification of Decorative Patterns in the Minoan Pottery of Kamares Style." In Geographic Information Systems: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 1132-1150. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2038-4.ch068

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Abstract

An important feature of the Minoan culture is the pottery of Kamares style, that documents the Cretan cultural production between the first half of the 2nd millennium BC. This high level painted production, characterized by the combination of several diverse motifs, presents an enormous decorative repertoire. The extraordinary variety of combinations between elementary motifs according to a complex visual syntax makes interesting the automatic identification of the motifs, particularly upon potsherds. A complete pipeline to accomplish this task is still a challenge to Computer Vision and Pattern Recognition. Starting from a digital image ROI identification, motif extraction, robust contour detection should be performed to obtain a bag of digital shapes. In a second phase each of the extracted shapes has to be classified according to prototypes in a database produced by an expert. The co-occurrence of the different shapes in a specimen will, in turn, be used to help the archaeologists in the cultural and even chronological setting.

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