Edge detection with Canny, LoG/zero-crossing, and wavelets

Edge detection is a preprocessing technique where the input is typically a two-dimensional (grayscale) image and the output is a set of curves (that are called the edges). The pixels that construct the edges in an image are the ones where there are sudden rapid changes (discontinuities) in the image intensity function, and the goal of edge detection is to identify these changes. Edges are typically detected by finding the local extrema of the first derivative (gradient) or by finding the zero-crossings of the second derivative (Laplacian) of the image. In this recipe, we will first implement two very popular edge detection techniques, namely, Canny and Marr-Hildreth (LoG with Zero crossings). Then, we will implement wavelet-based edge detection.

...