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Tessella-oriented segmentation and guidelines estimation of ancient mosaic images

[+] Author Affiliations
Lamia Benyoussef

Institut Fresnel (CNRS UMR 6133), GSM Group and École Centrale Marseille, Technopôle de Château-Gombert, 8, rue Frédéric Joliot Curie, 13451 Marseille Cedex 20, France

Stéphane Derrode

Institut Fresnel (CNRS UMR 6133), GSM Group and École Centrale Marseille, Technopôle de Château-Gombert, 8, rue Frédéric Joliot Curie, 13451 Marseille Cedex 20, France

J. Electron. Imaging. 17(4), 043014 (November 18, 2008). doi:10.1117/1.3013543
History: Received January 17, 2008; Revised August 28, 2008; Accepted September 25, 2008; Published November 18, 2008
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Automatic segmentation and analysis of ancient mosaic images can help archaeologists and experts build digital collections and automatically compare mosaics by means of image database indexing and content-based retrieval tools. However, ancient mosaics are characterized by low contrast colors and irregular tessella shape, orientation, and positioning, making automatic segmentation difficult. We propose a tessella-oriented strategy whose first step consists of isolating tessellas from their cemented network by computing the watershed transformation of a criterion image generated to exhibit the cement network as watershed crests. Then a simple k-means algorithm is used to classify tessellas and segment mosaic images with more accuracy than with a pixel-oriented strategy. Additionally, we propose a method to automatically obtain the main directional guidelines of mosaics by estimating tessella orientation. This is done by minimizing a contextual energy computed from gray-level means of neighboring tessellas and the orientation of their borders. Several examples of cartographies show the effectiveness of the method.

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© 2008 SPIE and IS&T

Citation

Lamia Benyoussef and Stéphane Derrode
"Tessella-oriented segmentation and guidelines estimation of ancient mosaic images", J. Electron. Imaging. 17(4), 043014 (November 18, 2008). ; http://dx.doi.org/10.1117/1.3013543


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