PCB fault detection using Image Processing
In this project, various concentrated works on the detection of defects on printed circuit boards (PCBs) have been done, but it is also crucial to classify these defects in order to analyze and identify the root causes of the defects.
This project is aimed at detecting and classifying the defects on bare single-layer PCBs by introducing a hybrid algorithm by combining the research done by Hermansyah et al and Khalid.
This project proposes a PCB defect detection and classification system using a morphological image segmentation algorithm and simple image processing theories.
Based on initial studies, some PCB defects can only exist in certain groups. Thus, it is obvious that the image processing algorithm could be improved by applying a segmentation exercise.
This project uses template and test images of a single layer, bare, grayscale computer-generated PCBs. PCB fault detection using Image Processing