Computational system to detect defects in mounted and bare PCB Based on connectivity and image correlation

In this paper we present an image analysis system for printed circuit board (PCB) automated inspection. In the last years PCB manufacturing industry has been advanced in inspection automation systems, especially to solve smaller tolerance requirements. A PCB consists in a circuit and electronic components assembled in a surface. There are three main process involved in its manufacture, where the inspection is necessary. The main process consists in the printing itself. Another important procedure is the components placement over the PCB surface. And the third is the components soldering. In the proposed inspection system we consider the board printing and components placements defects. We first compare a PCB standard image with a PCB image, using a simple subtraction algorithm that can highlight the main problem-regions. Then we used connection analysis in the printed circuit to find fatal and potential errors, like breaks, circuit shorts, missing components. Besides, using digital image correlation techniques, the system detects component errors, like absence, change, and wrong position. In other to develop this methodology in real PCB, we propose to magnify the problem-regions and start to find the errors in a set of PCB sections, which are smaller than the main PCB image.