Automatic circle detection on images with an adaptive bacterial foraging algorithm

ABSTRACT

This article presents an algorithm for the automatic detection of circular shapes from complicated and noisy images. The algorithm is based on a recently developed swarm-intelligence technique, well known as the Bacterial Foraging Optimization (BFO). A new fuzzy objective function has been derived for the edge map of a given image. Minimization of this function with an adaptive version of the BFO algorithm leads to the automatic detection of circles on the image.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search
          Subjects: Heuristic methods

Additional Classification:
  G. Mathematics of Computing
  G.1 NUMERICAL ANALYSIS
      G.1.6 Optimization
          Subjects: Global optimization

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search
          Subjects: Control theory

General Terms:
Algorithms, Experimentation, Performance

Keywords:
bacterial foraging, object recognition, swarm intelligence