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Online course

Robotic Vision: Processing Images

How do computers process images? Learn about image processing and image features, and how robots can be programmed to see.

What’s the difference between a free course and an upgraded course?

Free:

  • Access to the course for its duration + 14 days, regardless of when you join (this includes access to articles, videos, peer review steps, quizzes)
  • No certificate

Upgraded:

  • Unlimited access to the course, for as long as it exists on FutureLearn (this includes access to articles, videos, peer review steps, quizzes)
  • A Certificate of Achievement when you complete the course

Find out more

Robotic Vision: Processing Images

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This course is part of the Robotic Vision program, which will enable you to skills in building robotic vision systems will become vital to developing the robots of the future.

Learn how images are processed and transformed to make a robot see.

Programming a robot to see requires knowing the principles of vision, mathematical knowledge and programming skills. We explore how computers process images, learning the operations required to process an image using MATLAB.

Robotic vision relies on identifying and extracting the features of an image to recognize a shape. You’ll identify the unique features of a shape and its perimeter. We look at some advanced image processing techniques: morphology; and transformations such as scaling and warping. We finish the course with a look at colour and light, and how robots see colour.

Skip to 0 minutes and 4 secondsRobots with a sense of vision are going to be able to perform lots of useful tasks in a great range of industries and applications, but before we can program our own robotic vision system we need to understand what a digital image is, how we get it into the computer and how we can process those individual images. For robotic vision an essential first step is to capture visual information in the form of a digital image and get that into a computer so that we can manipulate it and extract meaning from it. With MATLAB demonstrations and practical exercises you will learn the programming basics for required for processing images.

Skip to 0 minutes and 37 seconds Robotic vision is an exciting and challenging field to be involved in with applications that span a variety of industries and applications, from manufacturing to marine science and even mining. In this course we'll learn about image processing which is a fundamental part of robotic vision. You will have the opportunity to program some image processing algorithms yourself. So please come and join me in this course while you learn about the important fundamentals of robotic vision.

What topics will you cover?

  • How computers process images
  • Pixels, edges and regions
  • How images are processed – histograms, monadic operations such as gamma correction and thresholding, and diadic operations
  • Spatial operators such as kernels, Gaussian smoothing and edge detection
  • How to extract image features – binary blobs and blob hierarchy
  • Advanced image processing – morphology, scaling and image warping
  • How to find dominant lines
  • Properties of colour and light.

When would you like to start?

  • Date to be announced

What will you achieve?

By the end of the course, you'll be able to...

  • Describe how images are represented in a computer
  • Describe the purposes of different types of image processing and feature extraction operations
  • Demonstrate basic coding in MATLAB for image processing relevant to robotics

Who is the course for?

This course assumes that you are familiar with concepts from advanced high-school mathematics or undergraduate engineering.

The course also assumes knowledge of programming – this will help you understand some of the demonstrations in the videos and is required for the third course in the robotic vision program. This course uses the MATLAB programming language and environment, but your knowledge of programming in other languages can be easily transferred to MATLAB. You can familiarize yourself with MATLAB by enrolling in the MATLAB Onramp tutorial.

Please note that this course includes video content and other visual teaching methods. Blind and visually impaired students may need a helper.

What software or tools do you need?

This course contains many practice activities in MATLAB. However, you won’t need to download the MATLAB software to complete the course (although if you already have it you are welcome to use it). With support from MathWorks, free access to MATLAB will be provided for the duration of the course plus 30 days.

The MATLAB exercises are embedded within the course, or you can use a version of MATLAB Online for which you’ll be provided a log-in and instructions for importing the Machine Vision Toolbox for MATLAB. You don’t need to own a robot, or have a robot kit, to take this course.

Who will you learn with?

Peter Corke

Professor of Robotic Vision at QUT and Director of the Australian Centre for Robotic Vision (ACRV). Peter is also an IEEE fellow and on the editorial board of several robotics research journals.

James Sergeant

PhD Candidate with the Australian Centre for Robotic Vision researching towards robust visual object recognition to facilitate useful robotic tasks.

Edward Pepperell

Dr Pepperell completed his PhD in robotic vision at QUT in 2016, with a research focus in vision-based place recognition.

Obadiah Lam

Hello! I'm Obadiah, a sessional academic at Queensland University of Technology. I've taught robotics and control engineering courses and MOOCs, and have worked as a robotic vision researcher at QUT.

Who developed the course?

QUT is a leading Australian university ranked in the top 2% of universities worldwide by the 2015-16 Times Higher Education World University Rankings. Located in Brisbane, it attracts 47,000 students.

What’s the difference between a free course and an upgraded course?

Free:

  • Access to the course for its duration + 14 days, regardless of when you join (this includes access to articles, videos, peer review steps, quizzes)
  • No certificate

Upgraded:

  • Unlimited access to the course, for as long as it exists on FutureLearn (this includes access to articles, videos, peer review steps, quizzes)
  • A Certificate of Achievement when you complete the course

Find out more

Get extra benefits, upgrade this course. For $79 (+ shipping) you'll get:

Unlimited access

Upgrading will mean you get unlimited access to the course.

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  • Take the course at your own pace
  • Refer to the material at any point in future

If you’re taking a course for free you have access to the course for its duration + 14 days, regardless of when you join. If you upgrade the course you have access for as long as the course exists on FutureLearn.

Certificate of Achievement

Upgrading means you’ll receive a Certificate of Achievement when you complete the course.

Image certificate mobile

  • Prove your success when applying for jobs or courses
  • Celebrate your hard work
  • Display on your LinkedIn or CV

To receive a Certificate of Achievement you need to mark 90% of the steps on the course as complete.

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