Chaotic species based particle swarm optimization algorithms and its application in PCB components detection

Na Dong, Chun Ho Wu, Wai Hung Ip, Zeng Qiang Chen, Kai Leung Yung

Research output: Journal article publicationJournal articleAcademic researchpeer-review

12 Citations (Scopus)


An improved particle swarm optimizer using the notion of chaos and species is proposed for solving a template matching problem which is formulated as a multimodal optimization problem. Template matching is one of the image comparison techniques. This technique is widely applied to determine the existence, location and alignment of a component within a captured image in the printed circuit board (PCB) industry where 100% quality assurance is always required. In this research, an efficient auto detection method using a multiple templates matching technique for PCB components detection is described. The new approach using chaotic species based particle swarm optimization (SPSO) is applied to the multi-template matching (MTM) process. To test its performance, the proposed Chaotic SPSO based MTM algorithm is compared with other approaches by using real captured PCB images. The Chaotic SPSO based MTM method is proven to be superior to other methods in both efficiency and effectiveness.
Original languageEnglish
Pages (from-to)12501-12511
Number of pages11
JournalExpert Systems with Applications
Issue number16
Publication statusPublished - 15 Nov 2012


  • Chaos
  • Chaotic species based particle swarm optimization
  • Multi-template matching
  • Multimodal optimization
  • Particle swarm optimization
  • PCB components detection

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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