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Journal of Electronic Imaging

Tessella-oriented segmentation and guidelines estimation of ancient mosaic images
Author(s): Lamia Ben Youssef; Stephane Derrode
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Paper Abstract

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.

Paper Details

Date Published: 1 October 2008
PDF: 7 pages
J. Electron. Imaging. 17(4) 043014 doi: 10.1117/1.3013543
Published in: Journal of Electronic Imaging Volume 17, Issue 4
Show Author Affiliations
Lamia Ben Youssef, Ecole Centrale Marseille (France)
Stephane Derrode, Ecole Centrale Marseille (France)


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