Title of article :
3-D object segmentation using ant colonies
Author/Authors :
P. Cerello، نويسنده , , Piergiorgio and Christian Cheran، نويسنده , , Sorin and Bagnasco، نويسنده , , Stefano and Bellotti، نويسنده , , Roberto and Bolanos، نويسنده , , Lourdes and Catanzariti، نويسنده , , Ezio and De Nunzio، نويسنده , , Giorgio and Evelina Fantacci، نويسنده , , Maria and Fiorina، نويسنده , , Elisa and Gargano، نويسنده , , Gianfranco and Gemme، نويسنده , , Gianluca and Lَpez Torres، نويسنده , , Ernesto and Luca Masala، نويسنده , , Gian and Peroni، نويسنده , , Cristiana and Santoro، نويسنده , , Matteo، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2010
Pages :
15
From page :
1476
To page :
1490
Abstract :
3-D object segmentation is an important and challenging topic in computer vision that could be tackled with artificial life models. neler Ant Model (CAM), based on the natural ant capabilities of dealing with 3-D environments through self-organization and emergent behaviours, is proposed. lonies, 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. del 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.
Keywords :
image processing , 3-D object segmentation , Artificial life , ant colony
Journal title :
PATTERN RECOGNITION
Serial Year :
2010
Journal title :
PATTERN RECOGNITION
Record number :
1733393
Link To Document :
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