Image segmentation is the process of partitioning an image into distinct and meaningful regions.

The goal of image segmentation is to separate different objects or regions of interest from the background or each other.

Segmentation can be based on various properties such as color, intensity, texture, motion, or a combination of these.

There are two main types of image segmentation: semantic segmentation and instance segmentation.

Semantic segmentation aims to assign a class label to each pixel in the image, such as "car," "road," or "tree."

Instance segmentation takes semantic segmentation a step further by differentiating between individual instances of objects.

Popular techniques for image segmentation include thresholding, edge-based methods, region-based methods, and deep learning-based approaches.