Computing the Orientation of Hardware Components from Images using Traditional Computer Vision Methods

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


This paper introduces a methodology for precise object orientation determination using Principal Component Analysis, with robust performance under significant noise conditions. It validates the potential to mitigate the challenges associated with Axis-Aligned Bounding Boxes in smart manufacturing environments. The proposed approach paves the way for improved alignment in robotic grasping tasks, positioning it as a computationally efficient alternative to ML methods employing Oriented Bounding Boxes. The methodology demonstrated a maximum angle deviation of 3.5 degrees under severe noise conditions through testing with bolts in orientations of 0 to 180 degrees.
Original languageEnglish
Title of host publicationThe 39th International Manufacturing Conference
Subtitle of host publicationSmart Manufacturing: The Next Generation
Number of pages2
Publication statusAccepted/In press - 25 Aug 2023
EventThe 39th International Manufacturing Conference: Smart Manufacturing - The Next Generation - Ulster University, Magee Campus, Derry/Londonderry, Northern Ireland
Duration: 24 Aug 202325 Aug 2023


ConferenceThe 39th International Manufacturing Conference
Abbreviated titleIMC39 2023
Country/TerritoryNorthern Ireland
Internet address

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  • Manufacturing
  • Vision
  • PCA
  • Machine Learning


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