TY - JOUR
T1 - Inspection technology to facilitate automated quality control of highly specular, smooth coated surfaces
AU - Parker, Johné M.
AU - Cheong, Yew Lim
AU - Gnanaprakasam, Pradeep
AU - Hou, Zhen
AU - Istre, Joseph
PY - 2002
Y1 - 2002
N2 - 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.
AB - 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.
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U2 - 10.1109/ROBOT.2002.1013618
DO - 10.1109/ROBOT.2002.1013618
M3 - Article
AN - SCOPUS:0036058546
SN - 1050-4729
VL - 3
SP - 2567
EP - 2574
JO - Proceedings-IEEE International Conference on Robotics and Automation
JF - Proceedings-IEEE International Conference on Robotics and Automation
ER -