Evolving PCB visual inspection programs using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Xie:2013:IVCNZ,

• author = "Feng Xie and Anh Hoang Dau and Alexandra L. Uitdenbogerd and Andy Song",
• booktitle = "28th International Conference of Image and Vision Computing New Zealand (IVCNZ 2013)",
• title = "Evolving PCB visual inspection programs using genetic programming",
• year = "2013",
• month = nov,
• pages = "406--411",
• keywords = "genetic algorithms, genetic programming, machine vision, defect detection, printed circuit board, automatic optical inspection",
• DOI = "doi:10.1109/IVCNZ.2013.6727049",
• ISSN = "2151-2191",
• 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 Genetic-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.",
• notes = "Also known as \cite{6727049}",

}

Genetic Programming entries for Feng Xie Anh Hoang Dau Alexandra L Uitdenbogerd Andy Song

Citations