Imagine a scene with bright objects against a dark background. Thresholding is a very common monadic operation which transforms the image into one where the pixels have two possible values: true or false which correspond to foreground or background. It can be performed with a single vectorized MATLAB operation.
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There are a lot of pixels in a typical image which makes them take up a lot of memory. Images can be compressed to take up less storage. Compression can be lossless or lossy, where we tradeoff size for quality.
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.
Let’s look at numerical approaches to inverse kinematics for a couple of different robots and learn some of the important considerations. For RTB10.x please note that the mask value must be explicitly preceded by the ‘mask’ keyword. For example: >> q = p2.ikine(T, [-1 -1], ‘mask’, [1 1 0 0 0 0])
Robots today are ubiquitous in manufacturing but they can do much, much more.
Frequently we want a trajectory that moves smoothly through a series of points without stopping.