Accurate image registration method for PCB defects detection

Abstract

Image registration technology has been widely used in many parts of the computer vision system such as the automatic optical inspection system which is used to detect the printed circuit board (PCB) defects. The accuracy of the image registration will deeply influence the system's performance, so this study proposed an accurate image registration algorithm and applied it to the PCB defect detection. Good features to track feature detector and speeded up robust feature descriptor are combined to extract efficient features to achieve the first accurate image registration. Afterwards, cross-correlation functions were used to compute the shift between the reference image and the first-registered image for further accurate registration. Experimental results show that the authors’ algorithm performs a much better registration, with a lower root-mean-square error value between the reference image and transformed image. What is more, they applied it to detect the defects of PCB with a high accuracy.