Diadic operations involve two images of the same size and result in another image. For example adding, subtracting or masking images. As a realistic application we look at green screening to superimpose an object into an arbitrary image.
Search Results for: image processing
We will extend our coverage of image processing. We will some previously discussed techniques in more depth, and introduce some additional ones.
Once a digital image exists as a matrix in the MATLAB workspace we can manipulate it to extract information that a robot could use. We will discuss some fundamental algorithms that operate on single images.
An important class of operations are monadic, which map an input image to an output image of the same size by applying the same function to every pixel.
Let’s recall the key techniques we’ve covered including monadic and dyadic image processing operations and efficient ways to write these in MATLAB using vectorization.
Let’s recap the important points from the topics we have covered in advanced image processing.
We will compare and contrast the terms image processing, computer vision and robotic vision — they have much in common but there are some subtle but important distinctions. When it comes to interpreting an image we typically try to find and describe regions, lines and interest points.
If we want to process images the first thing we need to do is to read an image into MATLAB as a variable in the workspace. What kind of variable is an image? How can we see the image inside a variable? How do we refer to to individual pixels within an image.