An optimization algorithm for shape analysis of regular polygons

Jen Ming Chen, Jose A. Ventura, Brian J. Melloy

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Machine vision has the potential to impact both quality and productivity significantly in computer integrated manufacturing due to its versatility, flexibility, and relative speed. Unfortunately, algorithm development has not kept pace with the advances in vision-hardware technology, particularly in the areas of analysis and decision making. The specific subject of this investigation is the development of a machine-vision algorithm for the dimensional checking, pose estimation, and overall shape verification of regular polygonal objects (e.g., surface-mounted electronic components and fastener heads). Algorithmically, the image boundary data is partitioned into n segments, and then a non-ordinary least squares technique is used to find the best fitting polygon. The algorithm is well-suited for online implementation in an automated environment due to its flexibility and demonstrated speed.

Original languageEnglish
Pages (from-to)82-92
Number of pages11
JournalMachine Vision and Applications
Issue number2
StatePublished - Jun 1994


  • Least-squares fitting
  • Modelbased inspection
  • Optimization
  • Regular polygons
  • Vision systems


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