Search Results for: morphological operation

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. […]

Let’s recap the important points about spatial operators. Linear operators can be used to smooth images and determine gradients. Template matching can be used to find a face in a crowd. Non-linear operators such as rank filters can be used for noise removal, and mathematical morphology treats shapes according to their compatibility with a structuring […]

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.

We will use Simulink to create a dynamic model of a single robot joint and simulate its operation.

Mathematical morphology comprises operations such as erosion, dilation, opening and closing. Let’s look at how we can use different shaped structuring elements to solve complex problems.

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.

Let’s recap the important points from the topics we have covered in advanced image processing.

We will extend our coverage of image processing. We will some previously discussed techniques in more depth, and introduce some additional ones.

We introduce spatial operators by a simple example of taking the average value of all pixels in a box surrounding each input pixel. The result is a blurring or smoothing of the input image.

Images contain many pixels and the normal way to process them is with nested for loops that index each pixel in turn. This is slow and somewhat cumbersome to write. MATLAB has a facility called vectorization that allows us to perform complex matrix operations without any loops.