Search Results for: pixel size

Let’s look at some simple monadic functions such as type conversion, brightness and contrast adjustment, inversion and posterisation and the effect they have on an image.

There is a lot of information in an image which we need to summarize somehow. An intensity histogram is one form of summary that provides useful information about how well the exposure of our camera is adjusted.

Let’s recap some of the most important topics we’ve covered about treating an image as a matrix within MATLAB which we can display or index into.

We use MATLAB and some Toolbox functions to create a robot controller that moves a camera so the image matches what we want it to look like. We call this an image-based visual servoing system.

The relationship between world coordinates, image coordinates and camera spatial velocity has some interesting ramifications. Some very different camera motions cause identical motion of points in the image, and some camera motions leads to no change in the image at all in some parts of the image. Let’s explore at these phenomena and how we […]

Given two images of a scene taken from slightly different viewpoints, a stereo image pair, it’s possible to determine the disparity for every pixel using template matching. The disparity image is one where the value of each pixel is inversely related to the distance between that point in the scene and the camera.

An image contains a huge amount of pixel data, and a video stream is a massive flow of pixel data. Typically a robot has only a few inputs, the position or velocity of its joints. How do we go from all that camera data to the small amount of data the robot really needs?

A robot can use a camera to capture an image of the world. The image contains millions of pixels, but the value of each pixel is not particularly informative about what’s present in the scene. We need a more concise or ‘higher level’ way to represent the information, and this is what we refer to […]

Another non-linear operation on the pixels in the box around the input pixel is to test whether they match a reference shape. This is a very powerful and useful approach to cleaning up noisy binary images known as mathematical morphology and objects in the image are treated according to their compatibility with a structuring element. […]

We will consider a very powerful group of functions, spatial operators, where each output pixel is a function of the corresponding input pixel and its neighbours.