Jakkrit Onshaunjit, Jakkree Srinonchat*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 355-367, 2022, DOI:10.32604/cmc.2022.017698
Abstract An ideal printed circuit board (PCB) defect inspection system can detect defects and classify PCB defect types. Existing defect inspection technologies can identify defects but fail to classify all PCB defect types. This research thus proposes an algorithmic scheme that can detect and categorize all 14-known PCB defect types. In the proposed algorithmic scheme, fuzzy c-means clustering is used for image segmentation via image subtraction prior to defect detection. Arithmetic and logic operations, the circle hough transform (CHT), morphological reconstruction (MR), and connected component labeling (CCL) are used in defect classification. The algorithmic scheme achieves 100% defect detection and 99.05%… More >
Login
Register
