Title :
Evolving PCB visual inspection programs using genetic programming
Author :
Feng Xie ; Anh Hoang Dau ; Uitdenbogerd, Alexandra L. ; Song, Andrew
Author_Institution :
Sch. of Comput. Sci. & IT, RMIT Univ., Melbourne, VIC, Australia
Abstract :
Automated optical inspection (AOI) is desirable in printed circuit board (PCB) manufacturing as inspecting manually is time-consuming and error-prone. This paper presents a study on evolving an AOI program with Genenetic-Programming (GP), an evolution-inspired technique. Using a GP-based approach, domain knowledge such as board design and lighting conditions are not required. Conventional feature extraction processes can also be avoided. The result demonstrates the evolved program capability to detect flaws under varied scenarios. Furthermore, it can be readily applied on different types of images without calibration or re-training.
Keywords :
automatic optical inspection; computer vision; electronic design automation; flaw detection; genetic algorithms; printed circuit design; printed circuit manufacture; production engineering computing; visual programming; AOI program; GP-based approach; PCB visual inspection programs; automated optical inspection; defect detection; evolution-inspired technique; flaw detection; genetic programming; machine vision; printed circuit board manufacturing; Accuracy; Feature extraction; Genetic programming; Image quality; Image resolution; Inspection; Lighting; automatic optical inspection; defects detection; genetic programming; machine vision; printed circuit board;
Conference_Titel :
Image and Vision Computing New Zealand (IVCNZ), 2013 28th International Conference of
Conference_Location :
Wellington
Print_ISBN :
978-1-4799-0882-0
DOI :
10.1109/IVCNZ.2013.6727049