3-D object segmentation using ant colonies
2009; Elsevier BV; Volume: 43; Issue: 4 Linguagem: Inglês
10.1016/j.patcog.2009.10.007
ISSN1873-5142
AutoresP. Cerello, Sorin Christian Cheran, S. Bagnasco, R. Bellotti, Lourdes Bolaños, Ezio Catanzariti, Giorgio De Nunzio, M.E. Fantacci, E. Fiorina, G. Gargano, G. Gemme, E. López Torres, Giovanni Luca Masala, C. Peroni, Matteo Santoro,
Tópico(s)Evolutionary Algorithms and Applications
Resumo3-D object segmentation is an important and challenging topic in computer vision that could be tackled with artificial life models. A Channeler Ant Model (CAM), based on the natural ant capabilities of dealing with 3-D environments through self-organization and emergent behaviours, is proposed. Ant colonies, defined in terms of moving, pheromone laying, reproduction, death and deviating behaviours rules, is able to segment artificially generated objects of different shape, intensity, background. The model depends on few parameters and provides an elegant solution for the segmentation of 3-D structures in noisy environments with unknown range of image intensities: even when there is a partial overlap between the intensity and noise range, it provides a complete segmentation with negligible contamination (i.e., fraction of segmented voxels that do not belong to the object). The CAM is already in use for the automated detection of nodules in lung Computed Tomographies.
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