TY - JOUR
T1 - Research on Printing Defects Inspection of Solder Paste Images
AU - Qi, Min
AU - Yin, Ting
AU - Cheng, Gong
AU - Xu, Yuelei
AU - Meng, Hongying
AU - Wang, Yi
AU - Cui, Shanshan
N1 - Publisher Copyright:
© 2022 Min Qi et al.
PY - 2022
Y1 - 2022
N2 - Solder paste printing is the first part of the surface mount process flow; its postprinting defect inspection is particularly important. In this paper, we focus on studying the printing defects inspection algorithm for solder paste on PCB (Printed Circuit Board) images. The work proposes a number of methods to enhance the defects inspection performance of solder paste printing: A regional multidirectional data fusion image interpolation method, which can achieve fast and high precision image interpolation; a method for detecting solder paste areas with better accuracy, efficiency, and robustness; an improved connected domain labeling method to reduce time complexity; and defects detection and types classification method, which extracts features and centroid of every solder paste region and completes the inspection by comparing with a standard image. The experiments show that the defects inspection algorithm can detect the most common types of defects with low time consumption, high inspection accuracy, and classification accuracy.
AB - Solder paste printing is the first part of the surface mount process flow; its postprinting defect inspection is particularly important. In this paper, we focus on studying the printing defects inspection algorithm for solder paste on PCB (Printed Circuit Board) images. The work proposes a number of methods to enhance the defects inspection performance of solder paste printing: A regional multidirectional data fusion image interpolation method, which can achieve fast and high precision image interpolation; a method for detecting solder paste areas with better accuracy, efficiency, and robustness; an improved connected domain labeling method to reduce time complexity; and defects detection and types classification method, which extracts features and centroid of every solder paste region and completes the inspection by comparing with a standard image. The experiments show that the defects inspection algorithm can detect the most common types of defects with low time consumption, high inspection accuracy, and classification accuracy.
UR - https://www.scopus.com/pages/publications/85128178286
U2 - 10.1155/2022/8651956
DO - 10.1155/2022/8651956
M3 - 文章
AN - SCOPUS:85128178286
SN - 1530-8669
VL - 2022
JO - Wireless Communications and Mobile Computing
JF - Wireless Communications and Mobile Computing
M1 - 8651956
ER -