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Memorias de investigación
Communications at congresses:
Image Segmentation Using Ant System-based Clustering Algorithm
Year:2011
Research Areas
  • Engineering
Information
Abstract
Industrial applications of computer vision sometimes require detection of atypical objects that occur as small groups of pixels in digital images. These objects are difficult to single out because they are small and randomly distributed. In this work we propose an image segmentation method using the novel Ant System-based Clustering Algorithm (ASCA). ASCA models the foraging behaviour of ants, which move through the data space searching for high data-density regions, and leave pheromone trails on their path. The pheromone map is used to identify the exact number of clusters, and assign the pixels to these clusters using the pheromone gradient. We applied ASCA to detection of microcalcifications in digital mammograms and compared its performance with state-of-the-art clustering algorithms such as 1D Self-Organizing Map, k-Means, Fuzzy c-Means and Possibilistic Fuzzy c-Means. The main advantage of ASCA is that the number of clusters needs not to be known a priori. The experimental results show that ASCA is more efficient than the other algorithms in detecting small clusters of atypical data.
International
Si
Congress
International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2011
960
Place
Salamanca, Spain
Reviewers
Si
ISBN/ISSN
1867-5662
10.1007/978-3-642-19644-7_62
Start Date
06/04/2011
End Date
08/04/2011
From page
35
To page
45
Proc. of the International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2011, Advances in Intelligent and Soft Computing, 2011, Volume 87/201
Participants
  • Autor: Aleksandar Jevtic (Robbosoft (Francia))
  • Autor: Joel Quintanilla Dominguez (UPM)
  • Autor: Diego Andina De la Fuente (UPM)
  • Autor: Jose Miguel Barron Adame (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Automatización en Señal y Comunicaciones (GASC)
  • Departamento: Señales, Sistemas y Radiocomunicaciones
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