Segmentation of Mosaic Images based on Deformable Models using Genetic Algorithms
Alberto Bartoli, Gianfranco Fenu, , 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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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.