Summary
In this chapter, we first discussed edge detection of images using several filters (Sobel, Prewitt, Canny, and so on) and by computing the gradient and Laplacian of an image. Then, we discussed LoG/DoG operators and how to implement them and detect edges with zero-crossing. Next, we discussed how to compute image pyramids and use Laplacian pyramids to blend two images smoothly. Finally, we discussed how to detect blobs with scikit-image. On completion of this chapter, the reader should be able to implement edge detectors (Sobel, Canny, and so forth) in an image with Python using different filters. Also, the reader should be able to implement filters to sharpen an image, and find edges at different scales using LoG/DoG. Finally, they should be able to blend images with Laplacian/Gaussian pyramids and implement blob detection in an image at different scale-spaces. In the next chapter, we shall discuss feature detection and extraction techniques from images.
