Automated inspection of printed circuit boards through machine vision

Abstract This paper introduces the development of an automated visual inspection system for printed circuit boards (PCBs). It utilizes an elimination-subtraction method which directly subtracts the template image from the inspected image, and then conducts an elimination procedure to locate defects in the PCB. Each detected defect is subsequently classified into one of the seven defect types by three indices: the type of object detected, the difference in object numbers, and the difference in background numbers between the inspected image and the template. Finally, a 256 × 240 PCB image was tested to show the effectiveness of this system.