Image Segmentation is a machine learning technique that splits an image into pixels and proceeds to analyze each pixel in the image and assigns a predetermined class to each pixel or group of pixels. An images annotated pixels are all members of the same class. Because it demands pixel-level accuracy, it is frequently used to label images for applications that call for great accuracy and involve a lot of manual labor. It can take up to 30 minutes or more to finish one photograph. An image is divided into several segments by the process of image segmentation. A mask or a labeled image serves as the representation for this group of segments. By doing this, we can process only the crucial portions of the image as opposed to the complete image.

Although machine learning has started to become a key part in research, researchers face challenges when using these types of machine learning. The most common challenges in machine learning include: lack of quality data, data compatibility, and a gap in machine learning knowledge.