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What is PCB Defect Detection and Classification Algorithm about?

This research presents an algorithmic scheme for the concurrent detection and classification of 14 known printed circuit board (PCB) defect types, achieving 100% defect detection and 99.05% classification accuracy. The method utilizes fuzzy c-means clustering for image segmentation, along with various image processing techniques such as the circle Hough transform and morphological reconstruction for defect classification. The proposed system enhances PCB manufacturing processes by accurately identifying def

Author

bruce lee

Language

EN