A New Swarm Intelligence Coordination Model Inspired by Collective Prey Retrieval and Its Application to Image Alignment

  • G. Da San Martino
  • F. A. Cardillo
  • A. Starita
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4193)


Swarm Intelligence is the emergent collective intelligence of groups of simple agents acting almost independently. Algorithms following this paradigm have many desirable properties: flexibility, decentralized control, robustness, and fault tolerance. This paper presents a novel agent coordination model inspired by the way ants collectively transport large preys. In our model a swarm of agents, each having a different destination to reach, moves with no centralized control in the direction indicated by the majority of agents keeping its initial shape. The model is used to build an algorithm for the problems of image alignment and image matching. The novelty of the approach and its effectiveness are discussed.


Particle Swarm Optimization Prefer Destination Swarm Intelligence Large Prey Speckle Noise 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • G. Da San Martino
    • 1
  • F. A. Cardillo
    • 2
  • A. Starita
    • 2
  1. 1.Dept. of Pure and Applied MathematicsUniversity of PadovaItaly
  2. 2.Dept. of Computer ScienceUniversity of PisaItaly

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