Segmentation of Mosaic Images based on Deformable Models using Genetic Algorithms




Alberto Bartoli, Gianfranco Fenu, Eric Medvet, Felice Andrea Pellegrino, Nicola Timeus


2nd EAI International Conference on Smart Objects and Technologies for Social Good (GOODTECHS), held in Venezia (Italy)



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Abstract #

Preservation and restoration of ancient mosaics is a crucial activity for the perpetuation of cultural heritage of many countries. Such an activity is usually based on manual procedures which are typically lengthy and costly. Digital imaging technologies have a great potential in this important application domain, from a number of points of view including smaller costs and much broader functionalities. In this work, we propose a mosaic-oriented image segmentation algorithm aimed at identifying automatically the tiles composing a mosaic based solely on an image of the mosaic itself. Our proposal consists of a Genetic Algorithm, in which we represent each candidate segmentation with a set of quadrangles whose shapes and positions are modified during an evolutionary search based on multi-objective optimization. We evaluate our proposal in detail on a set of real mosaics which differ in age and style. The results are highly promising and in line with the current state-of-the-art.