Abstract: Various examples described herein include various mechanisms, techniques, and methods to subtract collected signals caused by a periodic pattern formed on substrates to enable a higher level of defect detection on substrates. Signals detected by various types of metrology and substrate-inspection systems that are caused by periodic patterns on inspected substrates can be reduced or eliminated by, for example, a Fourier analysis of the detected signals. Both gray-scale value thresholds and area thresholds may be applied after the Fourier analysis of the image and are sufficient for defect detection on an image with a substantially-reduced number of false defects or no defects being present in a final image produced after processing. Other techniques and methods are also disclosed.

Abstract: Disclosed herein are examples of defect detection techniques for inspecting semiconductor devices, such as CMOS image sensors, during the manufacturing process. The defects can include common defects, such as scratches, dirt, etc., as well as low-contrast defects, such as watermarks. The detection technique may use a supervised machine learning network.