Tessella-oriented segmentation and guidelines estimation of ancient mosaic images

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 graylevel means of nei...

• Type: Journal
• Year: 2008
• Where: JEI
• Authors: Lamia Benyoussef, Stéphane Derrode
• Keywords: Ancient Mosaics, Automatic Segmentation, JEI 2008, Mosaics