2022
DOI: 10.1117/1.jei.32.1.011002
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Center detection algorithm for printed circuit board circular marks based on image space and parameter space

Abstract: A highly efficient circle positioning algorithm, called the two-step optimization Hough transform (TSHT), based on multi-resolution segmentation is proposed to solve the problems of the offset Hough transform, namely, its large memory overhead, long time consumption, and low recognition accuracy. First, using the image feature of the printed circuit board (PCB) circular identifier, the target circle is obtained using adaptive image preprocessing, and then, images of an acceptable quality are separated by shape… Show more

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Cited by 3 publications
(2 citation statements)
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“…In complex backgrounds, the model of YOLOv5s was more accurate than the detection of Hoff variations and was faster. In order to solve the problems of large memory overhead, long time consumption and low recognition accuracy of offset Hough transform, slam, N. et al [76] proposed an efficient circle localization algorithm based on multi-resolution segmentation (two-step optimized Hough transform). First, the target circle was obtained by adaptive image preprocessing to determine the location of the effective search area.…”
Section: Spatial Context Featurementioning
confidence: 99%
“…In complex backgrounds, the model of YOLOv5s was more accurate than the detection of Hoff variations and was faster. In order to solve the problems of large memory overhead, long time consumption and low recognition accuracy of offset Hough transform, slam, N. et al [76] proposed an efficient circle localization algorithm based on multi-resolution segmentation (two-step optimized Hough transform). First, the target circle was obtained by adaptive image preprocessing to determine the location of the effective search area.…”
Section: Spatial Context Featurementioning
confidence: 99%
“…However, the key to the detection method is just a specific state. Therefore, relying on the original anchor boxes dimensions does not meet the practical needs of PCB defect detection [12,13].…”
Section: Problem Statementmentioning
confidence: 99%