Graph-Based Segmentation is a technique used in image processing to divide an image into meaningful regions. It represents the image as a graph, where pixels are nodes and edges connect similar pixels based on color or intensity. This approach allows for the identification of distinct segments by analyzing the relationships between neighboring pixels. The method often employs algorithms like Normalized Cuts or Graph Cuts to optimize the segmentation process. By minimizing the cost of cutting the graph, these algorithms effectively separate different regions, making it easier to analyze and interpret images in various applications, such as computer vision and medical imaging.