Detection of Defects in Printed Circuit Boards by Clustering the Etalon and Defected Samples

Authors :: Roman Melnyk
Ruslan Tushnytskyy
Source :: 2020 IEEE 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET).
Publication Year :: 2020
Publisher :: IEEE, 2020.
Abstract: The K-mean clustering algorithm was implemented to find the PCB defects. Special procedure for image comparison was developed. Clustering helps not to notice small shifting and deviation of routine paths and contacts sizes and coordinates.

Subjects :: Printed circuit board
Computer science
business.industry
k-means clustering
Pattern recognition
Artificial intelligence
Cluster analysis
business
Fabry–Pérot interferometer
Image (mathematics)

Database :: OpenAIRE
Journal :: 2020 IEEE 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET)
Accession number :: edsair.doi...........73513de5100bc6fbfeb87964c575376b
Full Text :: https://doi.org/10.1109/tcset49122.2020.235580

Full Text Access

Tools