A physics-based defects model and inspection algorithm for automatic visual inspection

The representation of physical characteristics is the most essential feature of mathematical models used for the detection of defects in automatic inspection systems. However, the feature of defects and formation of the defect image are not considered enough in traditional algorithms. This paper presents a mathematical model for defect inspection, denoted as the localized defects image model (LDIM), is different because it modeling the features of manual inspection, using a local defect merit function to quantify the cost that a pixel is defective. This function comprises two components: color deviation and color fluctuation. Parameters related to statistical data of the background region of images are also taken into consideration. Test results demonstrate that the model matches the definition of defects, as defined by international industrial standards IPC-A-610D and IPC-A-600G. Furthermore, the proposed approach enhances small defects to improve detection rates. Evaluation using a defects images database returned a 100% defect inspection rate with 0% false detection. Proving that this method could be practically applied in manufacture to quantify inspection standards and minimize false alarms resulting from human error.