Autors: Slavov, D. V., Hristov, V. D.
Title: 3D Machine Vision System for Defect Inspection and Robot Guidance
Keywords: computer vision, defect hunting, visual inspection, machine learning

Abstract: This paper describes a vision system which can be used for defect inspection of machinery parts and guidance of industrial robots. The system is an important part of a conceptual production cell project. Based on the goal tasks, a 3D smart camera is selected. The appropriate sample for defect hunting is considered. Significance of the work scene lighting is emphasized and the built-in blue-light capabilities of the smart camera are indicated. Connection with a PC is established ensuring all needed communications. An application for visual inspection is developed which includes four building blocks and several techniques for measuring object characteristics. Convenient human-machine interface is built which allows fast system reconfiguration and project structure adjustment. Finally, essential propositions for further system improvement are outlined.



    IEEE 57th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST), 2022, Macedonia,

    Цитирания (Citation/s):
    1. H. F. Le, L. J. Zhang, Y. X. Liu, Surface Defect Detection of Industrial Parts Based on YOLOv5, 2022, IEEE Access, vol. 10, pp. 130784-130794, 2022, DOI: 10.1109/ACCESS.2022.3228687 - 2022 - в издания, индексирани в Scopus или Web of Science

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus