Image Segmentation is a computer vision technique that divides an image into meaningful regions or pixels based on their visual characteristics. Instead of simply identifying what objects are present, segmentation determines which specific pixels belong to each object or area. Machine learning and deep learning models analyze features such as color, texture, shape, and spatial relationships to create detailed pixel-level representations of an image.
Image Segmentation is commonly used in medical imaging, autonomous vehicles, satellite analysis, agriculture, robotics, and industrial inspection. Its purpose is to provide precise information about the location, shape, and boundaries of objects within visual data. For example, it can separate tumors from healthy tissue, distinguish roads from surrounding areas, identify crops in aerial imagery, or isolate defective components during manufacturing. This detailed visual understanding supports accurate measurement, automation, object tracking, and intelligent decision-making.
