Many smooth, highly specular coatings, such as automotive paints and appliance coatings, 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 step, this paper presents a cost-effective machine vision system design that utilizes surface reflectance models as a rational basis. Experimental and numerical investigations of diffuse angle images of specular coated surfaces confirm that these images yield a three-dimensional characterization of surface defects, efficiently, from a single image.
|Number of pages||12|
|Journal||Image and Vision Computing|
|State||Published - Mar 3 2009|
Bibliographical noteFunding Information:
This material is based upon work supported by the National Science Foundation, Division of Design, Manufacture and Industrial Innovation, under Grants DMI-9984867 and DMI-0074976, and Toyota Motor Manufacturing North America. The authors gratefully acknowledge undergraduate researcher James Casalino for his work in obtaining Eq. (7) and programming this equation on-board the DVT 530 to facilitate preliminary real-time studies.
- Camera calibration
- Defect characterization
- Surface quality of specular coatings
- Surface reflectance model
ASJC Scopus subject areas
- Signal Processing
- Computer Vision and Pattern Recognition