Automated Multiple View Inspection based on uncalibrated image sequences

Domingo Mery, Miguel Carrasco

Research output: Contribution to journalConference articlepeer-review

15 Scopus citations

Abstract

The Automated Multiple View Inspection (AMVI) has been recently developed for automated defect detection of manufactured objects. The approach detects defects by analysing image sequences in two steps. In the first step, potential defects are automatically identified in each image of the sequence. In the second step, the potential defects are tracked in the sequence. The key idea of this strategy is that only the existing defects (and not the false detections) can be successfully tracked in the image sequence because they are located in positions dictated by the motion of the test object. The AMVI strategy was successfully implemented for calibrated image sequences. However, it is not simple to implement it in industrial environments because the calibration process is a difficult task and unstable. In order to avoid the mentioned disadvantages, in this paper we propose a new AMVI strategy based on the tracking of potential detects in uncalibrated image sequences. Our approach tracks the potential defects based on a motion model estimated from the image sequence self. Thus, we obtain a motion model by matching structure points of the images. We show in our experimental results on aluminium die castings that the detection is promising in uncalibrated images by detecting 92.3% of all existing defects with only 0.33 false alarms per image.

Original languageEnglish
Pages (from-to)1238-1247
Number of pages10
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3540
DOIs
StatePublished - 2005
Event14th Scandinavian Conference on Image Analysis, SCIA 2005 - Joensuu, Finland
Duration: 19 Jun 200522 Jun 2005

Keywords

  • Automated visual inspection
  • Defect detection
  • Multiple view geometry

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