Research Article
Segmentation of Mosaic Images Based on Deformable Models Using Genetic Algorithms
@INPROCEEDINGS{10.1007/978-3-319-61949-1_25, author={Alberto Bartoli and Gianfranco Fenu and Eric Medvet and Felice Pellegrino and Nicola Timeus}, title={Segmentation of Mosaic Images Based on Deformable Models Using Genetic Algorithms}, proceedings={Smart Objects and Technologies for Social Good. Second International Conference, GOODTECHS 2016, Venice, Italy, November 30 -- December 1, 2016, Proceedings}, proceedings_a={GOODTECHS}, year={2017}, month={7}, keywords={Multi-objective optimization Cultural heritage Image processing}, doi={10.1007/978-3-319-61949-1_25} }- Alberto Bartoli
Gianfranco Fenu
Eric Medvet
Felice Pellegrino
Nicola Timeus
Year: 2017
Segmentation of Mosaic Images Based on Deformable Models Using Genetic Algorithms
GOODTECHS
Springer
DOI: 10.1007/978-3-319-61949-1_25
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 , 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.