Development of a visual inspection system for the detection of paint defects on car bodies
A recently published paper focuses on the development and validation of an algorithm for a surface inspection system, which improves the accuracy of detecting paint defects through an image processing system.
Once they are detected, a reliable classifier is necessary to gain further information about the paint defects. The generated data can be utilised for improving the paint application process and for identifying the perpetrator of the paint defects once the defect classification is operational.
As a consequence, the quality control circuit can be shortened, the surface quality of different paint formulae can be evaluated objectively, and actions can be taken in order to reduce the occurrences of certain defect types.
Visual inspection system for detecting paint defects
The paper presents the physical setup of the visual inspection system and a detailed description of the algorithm for detecting the defects in the acquired images. Further research is essential to generate a classifier to differentiate the types of paint defects.
The study is published in: Journal of Coatings Technology and Research July 2019, Volume 16, Issue 4, pp 1033–1042.
