Edges play a major role in both human and computer vision. We, as humans, can easily recognize many object types and their pose just by seeing a backlit silhouette or a rough sketch. Indeed, when art emphasizes edges and poses, it often seems to convey the idea of an archetype, such as Rodin's The Thinker or Joe Shuster's Superman. Software, too, can reason about edges, poses, and archetypes. We will discuss these kinds of reasoning in later chapters.
OpenCV provides many edge-finding filters, including Laplacian, Sobel, and Scharr. These filters are supposed to turn non-edge regions into black and turn edge regions into white or saturated colors. However, they are prone to misidentifying noise as edges. This flaw can be mitigated by blurring an image before trying to find its edges. OpenCV also provides many blurring filters, including blur (a simple...
