AFRC’s image processing platform : a high speed user-friendly architecture for real time object detection in forging processes

Kahani, Danial and Zante, Remi; Goh, Yee Mey and Case, Keith, eds. (2016) AFRC’s image processing platform : a high speed user-friendly architecture for real time object detection in forging processes. In: Advances in Manufacturing Technology XXX. Advances in Transdisciplinary Engineering . IOS Press, Amsterdam, pp. 205-210. ISBN 9781614996675 (https://doi.org/10.3233/978-1-61499-668-2-205)

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Abstract

Real-time detection and measurements of hot parts is desirable to permit real-time process control and automated part handling in harsh environments like forging and forming. The image processing platform described provides improved performance of Graphical User Interface (GUI), fast processing speed and integrity over industrial packages which are typically used in process control of forging processes or harsh manufacturing environments. A flexible, image processing software package for detecting objects in manufacturing environments has been developed at the Advanced Forming Research Centre (AFRC). The software consists of a set of image processing tools, written in MFC/C++ and OpenCV for Windows platforms. The software provides a powerful flowchart-based GUI for designing image processing algorithms. AFRC’s Image Processing Platform can be easily integrated with other industrial software packages like GE Proficy® using ActiveX technology. The package was successfully tested for real-time hot object detection inside a hot furnace in a forging environment.

ORCID iDs

Kahani, Danial ORCID: https://orcid.org/0000-0002-5011-380X

Zante, Remi ORCID: https://orcid.org/0000-0002-1179-1851

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• Item metadata

  Item type:	Book Section
  ID code:	57774
  Dates:	Date Event 8 September 2016 Published 23 May 2016 Accepted
  Subjects:	Technology > Engineering (General). Civil engineering (General) > Engineering design
  Department:	Faculty of Engineering > Design, Manufacture and Engineering Management
  Depositing user:	Pure Administrator
  Date deposited:	13 Sep 2016 10:56
  Last modified:	17 Dec 2024 01:03
  URI:	https://strathprints.strath.ac.uk/id/eprint/57774