Image segmentation is the process of separating an image into its constituent parts. It is an important step in many computer vision applications in the real world. There are many different ways of segmenting an image. When we segment an image, we separate the regions based on various metrics such as color, texture, location, and so on. All the pixels within each region have something in common, depending on the metric we are using. Let's take a look at some of the popular approaches here.

To start with, we will be looking at a technique called GrabCut. It is an image segmentation method based on a more generic approach called graph-cuts. In the graph-cuts method, we consider the entire image to be a graph, and then we segment the graph based on the strength of the edges in that graph. We construct the graph by considering each pixel to be a node and edges are constructed between the nodes, where edge weight is a function of the pixel values of those two nodes...