Mixed constrained image filter design using particle swarm optimization

Zhiguo Bao, Takahiro Watanabe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

This paper describes evolutionary image filter design for noise reduction using particle swarm optimization (PSO), where mixed constraints on the circuit complexity, power and signal delay are optimized. First, the evaluating values about correctness, complexity, power and signal delay are introduced to the fitness function. Then PSO autonomously synthesizes a filter. To verify the validity of our method, an image filter for noise reduction is synthesized. The performance of resultant filter by PSO is similar to that of Genetic Algorithm (GA), but the running time of PSO is 10% shorter than that of GA.

Original languageEnglish
Title of host publicationProceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10
Pages230-235
Number of pages6
Publication statusPublished - 2010 Dec 1
Event15th International Symposium on Artificial Life and Robotics, AROB '10 - Beppu, Oita, Japan
Duration: 2010 Feb 42010 Feb 6

Publication series

NameProceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10

Other

Other15th International Symposium on Artificial Life and Robotics, AROB '10
CountryJapan
CityBeppu, Oita
Period10/2/410/2/6

Keywords

  • Evolutionary design
  • Image filter
  • PSO

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

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  • Cite this

    Bao, Z., & Watanabe, T. (2010). Mixed constrained image filter design using particle swarm optimization. In Proceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10 (pp. 230-235). (Proceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10).