Inspection technology to facilitate automated quality control of highly specular, smooth coated surfaces

Johné M. Parker, Yew Lim Cheong, Pradeep Gnanaprakasam, Zhen Hou, Joseph Istre

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Many smooth, highly specular coatings, such as automotive paints, are subjected to considerable performance demands and manufacturers spend significant sums each year to monitor and repair coating surface quality. Additionally, changing product specifications and environmental regulations will continue to affect the processing parameters that influence surface appearance and quality. Therefore, it is vital to develop robust methods to monitor surface quality on-line and continuously examine the processes that significantly affect surface appearance in real time. As a critical first step, this paper presents a machine vision system design that utilizes surface reflectance models as a rational basis. Experimental and numerical investigations of specular and diffuse images of a range of specular coated surfaces confirm that these images efficiently yield information that corresponds strongly to human assessment and ranking.

Original languageEnglish
Pages (from-to)2567-2574
Number of pages8
JournalProceedings-IEEE International Conference on Robotics and Automation
Volume3
DOIs
StatePublished - 2002

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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