In image analysis, what is the purpose of semantic segmentation?

The purpose of semantic segmentation is to identify and classify individual pixels in an image, assigning a label to each pixel that reflects the object or region it belongs to. This technique enables a detailed understanding of the image's content by producing a pixel-wise mask that delineates different objects within the scene, such as distinguishing between a car, a pedestrian, and the background.

By analyzing images at the pixel level, semantic segmentation allows for more sophisticated applications in fields such as autonomous driving, medical imaging, and scene understanding, where precise delineation of objects is crucial. This method contrasts with broader classification tasks, which might categorize an entire image without addressing the specifics of object boundaries or identities.