Felzenszwalb’s Algorithm

Felzenszwalb’s Algorithm is a method for dividing an image into meaningful regions or segments based on color and intensity similarities. It starts by treating each pixel as its own region and then iteratively merges neighboring regions if the difference between them is small, considering the internal consistency of each region. This process continues until no more suitable merges can be made, resulting in a segmented image that groups similar areas together. It is efficient and adjustable, making it useful for tasks like object detection or image analysis by simplifying complex images into notable regions.