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The quiet revolution in machine vision - A state-of-the-art survey paper, including historical review, perspectives, and future directions

Smith, Melvyn L.; Smith, Lyndon N.; Hansen, Mark F.

Authors

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Melvyn Smith Melvyn.Smith@uwe.ac.uk
Research Centre Director Vision Lab/Prof

Lyndon Smith Lyndon.Smith@uwe.ac.uk
Professor in Computer Simulation and Machine

Mark Hansen Mark.Hansen@uwe.ac.uk
Associate Professor in Knowledge Exchange & External Engagement



Abstract

Over the past few years, what might not unreasonably be described as a true revolution has taken place in the field of machine vision, radically altering the way many things had previously been done and offering new and exciting opportunities for those able to quickly embrace and master the new techniques. Rapid developments in machine learning, largely enabled by faster GPU-equipped computing hardware, has facilitated an explosion of machine vision applications into hitherto extremely challenging or, in many cases, previously impossible to automate industrial tasks. Together with developments towards an internet of things and the availability of big data, these form key components of what many consider to be the fourth industrial revolution. This transformation has dramatically improved the efficacy of some existing machine vision activities, such as in manufacturing (e.g. inspection for quality control and quality assurance), security (e.g. facial biometrics) and in medicine (e.g. detecting cancers), while in other cases has opened up completely new areas of use, such as in agriculture and construction (as well as in the existing domains of manufacturing and medicine). Here we will explore the history and nature of this change, what underlies it, what enables it, and the impact it has had - the latter by reviewing several recent indicative applications described in the research literature. We will also consider the continuing role that traditional or classical machine vision might still play. Finally, the key future challenges and developing opportunities in machine vision will also be discussed.

Citation

Smith, M. L., Smith, L. N., & Hansen, M. F. (2021). The quiet revolution in machine vision - A state-of-the-art survey paper, including historical review, perspectives, and future directions. Computers in Industry, 130, https://doi.org/10.1016/j.compind.2021.103472

Journal Article Type Article
Acceptance Date Apr 28, 2021
Online Publication Date May 15, 2021
Publication Date Sep 1, 2021
Deposit Date Apr 30, 2021
Publicly Available Date May 16, 2023
Journal Computers in Industry
Print ISSN 0166-3615
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 130
Article Number 103472
DOI https://doi.org/10.1016/j.compind.2021.103472
Keywords machine vision; machine learning; deep learning; state-of-the-art
Public URL https://uwe-repository.worktribe.com/output/7319734
Publisher URL Elsevier