During the process of automobile manufacturing and transportation, it is inevitable to cause automobile surface defects, such as scratches, sunken, blots, and so on. This will seriously affect auto sales and lead to huge economic disputes between transportation companies and consumers. At present, manual detection is still the mainstream way of defect detection for automobile surfaces, which is unstable and time-consuming. This paper presents a defect detection method for automobile surfaces based on a lighting system with light fields. Fast, automated, and accurate location of surface defects can be achieved by using a high-quality defect imaging method based on light fields, the multi-exposure fusion algorithm, and the YOLO V5 network. For different materials or surfaces reflection characteristics, the proposed method can accurately detect various surface defects in areas such as doors, windshields, and wheel hubs.
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