The Channeler Ant Model: Object segmentation with virtual ant colonies

Autor: Lourdes Bolanos, Piergiorgio Cerello, G.L. Masala, Giorgio De Nunzio, Ezio Catanzariti, G. Gargano, S. C. Cheran, Matteo Santoro, Francesco Bagagli, Ernesto Lopez Torres, Elisa Fiorina, Stefano Bagnasco, Roberto Bellotti, Gianluca Gemme, Cristiana Peroni
Přispěvatelé: Cerello, Piergiorgio, Cheran, Sorin Christian, Bagagli, Francesco, Bagnasco, Stefano, Bellotti, Roberto, Bolanos, Lourde, Catanzariti, Ezio, DE NUNZIO, Giorgio, Fiorina, Elisa, Gargano, Gianfranco, Gemme, Gianluca, Lopez Torres, Ernesto, Masala, Gian Luca, Peroni, Cristiana, Santoro, Matteo
Rok vydání: 2008
Předmět:
Zdroj: 2008 IEEE Nuclear Science Symposium Conference Record.
DOI: 10.1109/nssmic.2008.4775019
Popis: 3-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).
Databáze: OpenAIRE