Image segmentation is a technique used in computer vision to separate images into different parts. One common method is image thresholding, which divides image intensities into two categories to create a binary image. This helps in analyzing images for tasks like medical imaging or object recognition. Different thresholding techniques work better for different types of images. Otsu's global thresholding is fast and effective for clear images, while using moving averages can improve results for images with noise. Hybrid techniques combining global and local thresholding can also be useful.