The Canny edge detector is an image processing technique used to identify edges in images. Developed by John F. Canny in 1986, it aims to provide good detection, localization, and minimal response to noise. The process involves several steps, including noise reduction, gradient calculation, non-maximum suppression, and edge tracking by hysteresis. First, the image is smoothed using a Gaussian filter to reduce noise. Then, the gradient of the image is calculated to find areas of rapid intensity change, which indicate potential edges. Finally, the algorithm uses thresholding to determine which edges are strong enough to be considered significant, resulting in a clear outline of objects within the image.