Robust automated multiple view inspection

Luis Pizarro, Domingo Mery, Rafael Delpiano, Miguel Carrasco

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Recently, Automated Multiple View Inspection (AMVI) has been developed for automated defect detection of manufactured objects, and the framework was successfully implemented for calibrated image sequences. However, it is not easy to be implemented in industrial environments because the calibration is a difficult and an unstable process. To overcome these disadvantages, the robust AMVI strategy, which assumes that an unknown affine transformation exists between each pair of uncalibrated images, is proposed. This transformation is estimated using two complementary robust procedures: a global approximation of the affine mapping is computed by creating candidate correspondences via B-splines and selecting those which better satisfy the epipolar constraint for uncalibrated images. Then, we use this approximation as initial estimate of a robust intensity-based matching approach, which is applied locally on each potential defect. The result is that false alarms are discarded, and the defects of an industrial object are actually tracked along the uncalibrated image sequence. The method is successful as shown in our experiments on aluminum die castings.

Original languageEnglish
Pages (from-to)21-32
Number of pages12
JournalPattern Analysis and Applications
Volume11
Issue number1
DOIs
StatePublished - Jan 2008

Keywords

  • Automated visual inspection
  • Image matching
  • Radioscopic imaging system
  • Robustness
  • Sequence tracking
  • Uncalibrated images
  • X-ray imaging

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