Parallel Strip Segment Recognition and Application to Metallic Tubular Object Measure

  • Nicolas Aubry
  • Bertrand KerautretEmail author
  • Isabelle Debled-Rennesson
  • Philippe Even
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9448)


The segmentation or the geometric analysis of specular object is known as a difficult problem in the computer vision domain. It is also true for the problem of line detection where the specular reflection implies numerous false positive line detection or missing lines located on the dark parts of the object. This limitation reduces its potential use for concrete industrial applications where metallic objects are frequent. In this work, we propose to overcome this limitation by proposing a new strategy which is not based on the image gradient as usually, but exploits the image intensity profile defined inside a parallel strip primitive. Associated to a digital straight segment recognition algorithm robust to noise, we demonstrate the efficiency of our proposed method with a real industrial application.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Nicolas Aubry
    • 1
    • 2
  • Bertrand Kerautret
    • 1
    • 2
    Email author
  • Isabelle Debled-Rennesson
    • 1
    • 2
  • Philippe Even
    • 1
    • 2
  1. 1.Université de Lorraine, LORIA, UMR 7503Vandoeuvre-lès-nancyFrance
  2. 2.CNRS, LORIA, UMR 7503Vandoeuvre-lès-nancyFrance

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