AN IMPROVED DEFECT CLASSIFICATION ALGORITHM FOR SIX PRINTING DEFECTS AND ITS IMPLEMENTATION ON REAL PRINTED CIRCUIT BOARD IMAGES

作者：Ibrahim Ismail^*; Ibrahim Zuwairie; Khalil Kamal; Mokji Musa Mohd; Abu Bakar Syed Abdul Rahman Syed; Mokhtar Norrima; Ahmad Wan Khairunizam Wan

来源：International Journal of Innovative Computing Information and Control, 2012, 8(5A): 3239-3250.

• Printed circuit boards
• Defect classification
• Defect detection

Because decisions made by human inspectors often involve subjective judgment, in addition to being intensive and therefore costly, an automated approach for printed circuit board (PCB) inspection is preferred to eliminate subjective discrimination and thus provide fast, quantitative, and dimensional assessments. In this study, defect classification is essential to the identification of defect sources. Therefore, an algorithm for PCB defect classification is presented that consists of well-known conventional operations, including image difference, image subtraction, image addition, counted image comparator, flood-fill, and labeling for the classification of six different defects, namely, missing hole, pinhole, underetch, short-circuit, open-circuit, and mousebite. The defect classification algorithm is improved by incorporating proper image registration and thresholding techniques to solve the alignment and uneven illumination problem. The improved PCB defect classification algorithm has been applied to real PCB images to successfully classify all of the defects.

• 出版日期2012-5