Pattern Recognition and Machine Learning
So far, so simple. Where it starts to get a little more complex is when we include Pattern Recognition into the family tree(Robot Vision's Family Tree | CrazyEngineers), or more broadly Machine Learning. This branch of the family is focused on recognizing patterns in data, which is quite important for many of the more advanced functions required of Robot Vision. For example, to be able to recognize an object from its image, the software must be able to detect if the object it sees is similar to previous objects. Machine Learning, therefore, is another parent of Computer Vision alongside Signal Processing.
However, not all Computer Vision techniques require Machine Learning. You can also use Machine Learning on signals which are not images. In practice, the two domains are often combined like this: Computer Vision detects features and information from an image, which are then used as an input to the Machine Learning algorithms. For example, Computer Vision detects the size and color of parts on a conveyor belt, then Machine Learning decides if those parts are faulty based on its learned knowledge about what a good part should look like.