Canny Edge Detection Algorithm

Image processing edge detection algorithms are computational techniques designed to identify boundaries within digital images. As fundamental tools in computer vision and image processing, these algorithms help isolate transitions between different image regions and serve critical applications including object detection, image segmentation, and feature extraction. Prominent edge detection methodologies include the Sobel operator, Canny detector, and Laplacian operator, which typically involve gradient-based filtering and derivative operations to locate intensity changes. From an implementation perspective, the Canny algorithm specifically follows a multi-stage pipeline: Gaussian smoothing for noise reduction, gradient magnitude calculation using Sobel kernels, non-maximum suppression for edge thinning, and double thresholding with hysteresis for edge linking. These algorithms enable more precise structural analysis and feature interpretation in digital images through systematic pixel-intensity variation detection.