MASTERCLASS

Getting images into a computer

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Transcript

In this lecture we're going to learn about how we get a digital image into a computer.  For robotic vision, this is the essential first step; we have to have the visual information inside the computer, so that we can manipulate it and eventually extract meaning from it, so this is the essential first step.

Digital images today are really common, they're everywhere.  Through billions and billions of images on Facebook and Flickr and shared through applications like Instagram.  There are a few reasons why digital images are so common today.

The first is that cameras are everywhere so the opportunities to take pictures are enormous.  We have cameras in our phones, in our tablet computers, in our laptops.  A large number of people are now starting to wear cameras on their heads photographing everything that they're seeing and experiencing, 24 by 7 perhaps.  The second reason why is that storage has become so cheap.  Low cost flash memory in our phones and in our laptop computers and terabytes of hard disk storage that you can buy for relatively little money today.  It wasn't always this way.  Ten years ago we were making the transition from chemistry to digital technology for picture taking.

In the bad old days of chemical imaging, we had to expose a number of frames on our film; we could never delete an image.  Once the film was full, we'd take it to the shop, we'd get it developed and we'd get our pictures back on paper.  It was way less flexible.  So what we're going to do in this lecture is work out and discuss how we get images from many, many digital sources, images from perhaps your photo library, perhaps from the web camera on your computer, perhaps from the web and getting those images into an environment where we can begin to manipulate them.

Digital images are everywhere: in your phone, on your hard drive, on the internet. We can access still pictures, movies and streams from live cameras all around the world. Let’s talk about digital images and how we can get them into the MATLAB environment where we can work on them.

Professor Peter Corke

Professor of Robotic Vision at QUT and Director of the Australian Centre for Robotic Vision (ACRV). Peter is also a Fellow of the IEEE, a senior Fellow of the Higher Education Academy, and on the editorial board of several robotics research journals.

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This content assumes only general knowledge.

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