Abstract
The paper describes the design, implementation, testing and validation of an open-source machine vision framework based on OpenCV (Open Source Computer Vision) library. This framework was developed for smart manufacturing control. Material conditioning and handling processes involving industrial robots are the processes that benefit from the proposed solution. The solution offers the following functionalities: acquisition of video streams from multiple sources, image analysis, object recognition, localization and interaction with industrial equipment using standard, open communication protocols. The paper covers several design aspects: system architecture, data acquisition and standardization of the image representation to be used by the analysis algorithms and object recognition module, input/output interaction protocols, camera-robot calibration. Results are reported for an implementation of the framework using a commercial image acquisition device and an industrial robot.
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Răileanu, S., Borangiu, T., Anton, F. (2021). An Open-Source Machine Vision Framework for Smart Manufacturing Control. In: Borangiu, T., Trentesaux, D., Leitão, P., Cardin, O., Lamouri, S. (eds) Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future. SOHOMA 2020. Studies in Computational Intelligence, vol 952. Springer, Cham. https://doi.org/10.1007/978-3-030-69373-2_3
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DOI: https://doi.org/10.1007/978-3-030-69373-2_3
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