Automatic Visual Inspection of PCB

A algorithm was developed to inspect printed circuit boards for defect detection and classification. Various computer vision techniques like image registration, denoising, segmentation and connected component analysis were used to detect and classify defects into all 14 classes.

Reseachers are welcome to use our dataset of PCB images with an understading to cite our work.

To access our dataset: [Dataset]

V. Chaudhary, I. Dave and K. Upla, "Automatic Visual Inspection of Printed Circuit Board for Defect Detection and Classification", in International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), Chennai, 2017, pp. 752-757. (DOI: 10.1109/WiSPNET.2017.8299858) (Scopus Indexed) (Full-text available) (Access Dataset)