What is Computer Vision and Machine Vision

Augmented Startups
A free video tutorial from Augmented Startups
M(Eng) AI Instructor 68k+ Subs on YouTube & 47k+ on Udemy
3.7 instructor rating • 19 courses • 51,379 students

Lecture description

In this lecture I define what is computer and machine vision. I also tell you the differences between machine and computer vision. The applications of computer vision are discussed as well as the endless possibilities of its uses.

Learn more from the full course

Learn Computer Vision and Image Processing in LabVIEW

Learn Computer Vision and Image Processing From Scratch in LabVIEW and build 9 Vision-based Apps

02:43:28 of on-demand video • Updated November 2019

  • Develop 9 Vision Based Apps in LabVIEW
  • Understand the fundamentals of Image Processing
  • The difference between computer and machine vision as well as their applications
  • Theory behind each image processing algorithm
  • How to apply the image processing algorithms for real life purposes
English [Auto] Have Guys welcome to the selection in this lecture we're going to be discussing what is machine vision and what is computer vision as well as the differences between the two. OK. So machine vision is that technology and methods used to provide imaging based automation inspection and then less analysis for applications such as automatic inspection Bruce's control and guidance control in industry. So you can basically think of it as use for inspection. So you can inspect basically wood materials different materials class wings for this one we can look at cells something small that can be detected by the human eye and basically integral parts of a bigger system. So it he said the primary uses for machine vision are automated inspection and industrial robot guidance and you can see a list of uses for machine vision looking at a more visual aspect. We can see if we have your favorite catcher and one is full to the brim. That's one you can see is obviously fold three quarters almost no. You might say that for a no person can spot this out easily. Why do you need a camera if you're turning over thousands and thousands of these bottles and these ones are streaming past. It will be quite hard to get a physical fixedness with cameras makes it much much easier. Looking over at this one we can also use machine vision for doing a similar function as the laser to detect it or it can detect the height and who are using cameras going over. This is a actual machine vision application where they use the machine vision to detect the diameter of the spanners and they can classify it in two different time it is. And then from this sort it out into 10 millimeters 20 millimeters whatever or they can use it to detect any cracks or any defects any defections that may cause the product not to work at its optimal performance. And Avia in PCB design a camera is used for visual inspection and then if the issue does not work according to the required specification it can push it out for the manufacturer or for the testing. OK so let's look at what is computer vision computer vision is a field that includes methods for acquiring processing analyzing and understanding images and in general higher dimensional data from the real world in order to produce numerical or symbolic information basically in forms of decisions. So how humans work we see OK the sky is all the sky is shot the sky is medium high. A camera can do something like that and do some sort of sorting. This not only applicable to people can be exposed to anything. So why are we learning computer vision. Well vision is built upon fields of mathematics physics biology engineering and of course computer science. There are many fields related to computer vision such as machine learning signal processing robotics and artificial intelligence. So even though it is a field built up on advanced concepts more and more tools are accessible to everyone from hobbyists division engineers to academic researchers. It is an important time in this field and there are endless amount of possibilities for these applications. One of the things that makes it very exciting is that these is the hardware requirements are inexpensive allowing you to more casually enter into this field. And it may open doors to new applications and innovations. So looking at a couple of applications of computer vision starting from left to right we can use it for object classification or detection so we can detect it. That's a car that's a horse. As a person we can do tracking and segment to only the horse maybe for Photoshop purposes and then we have people tracking. So we detect some people there are maybe in an airport in the street and we can do all sorts of tracking. Now we're tracking for maybe security see if person left the bag and you to see where that person meant to or how long a bag has been in the same position. It could be a bomb it could be a threat no one knows. So if a camera is that is always watching we'll be able to flag an alert saying that there is a potential threat for those who play Xbox or PlayStation. This X-Box connect or for Playstation There's the eye to it. It is actually picks up your motion through a camera and maybe an additional infrared camera and that can create a good skeletal model of you. And from that it will create a more augmented gaming experience. Looking at traffic monitoring these vehicle detection even under Section 4 like vision based adaptive cruise control systems Google uses this for creating the density of traffic. So a camera can see how much cars they are and maybe give you an alternative route based on the density of cars on a certain particular highway. OK. And then facial detection can be used for many purposes for it can range from the Boston crowd. So one could be a suspect or this could be a shoplifter staf you could use it for detecting terrorist can be used also for unlocking your computer. Your face. OK so in the phone industry it can be used for visual effects. Now instead of creating a whole suit of armor for us poor Robert Downey Jr. to wear you it will be really inconvenient or very hard for him to carry that heavy suit of armor whether it works or not. So instead to make it easier for him and to make it a more realistic you can use computer generated images and those computer generated images use this for digital markers as trackers. And so these trackers I used to overlay the Aymond suit on Robert Downey Jr. looking at the differences between computer vision and machine vision computer vision and machine vision are different terms for overlapping technologies. Computer Vision refers to the brought to capture and the automation of image analysis with the emphasis on the image analysis function across a wide range of theoretical and practical applications. Machine vision on the other hand traditionally refers to the use of computer vision in an industrial or practical application or process where it is necessary to execute a certain function or outcome based on image analysis done by the vision system. So if you look at it machine vision is basically a subsidiary of computer vision computer vision is one of the overlapping technologies that mission vision falls into. Ok so I hope you enjoyed this lecture. We're going to get that in the next lecture. We're going to be downloading lapu so that be consulted computer vision and mission vision applications. Also while you're looking to see these lectures if you feel that you're enjoying it or if you have learnt something from this course please go ahead and review and give good feedback on the scores. Please I would really appreciate it. And to really help other students find schools as well as help people collaborate in different machine vision applications. OK so I'll see you in the next lecture. Thank you for watching.