Summary

In this chapter, we discussed different image processing techniques based on mathematical morphology. We discussed morphological binary operations such as erosion, dilation, opening, closing, skeletonizing, and white and black top-hats. Then we discussed some applications such as computing the convex hull, removing small objects, extracting the boundary, fingerprint cleaning with opening and closing, filling holes in binary objects, and using opening and closing to remove noise. After that, we discussed extension of the morphological operations to grayscale operations and applications of morphological contrast enhancement, noise removal with the median filter, and computing local entropy. Also, we discussed how to compute the morphological (Beucher) gradient and the morphological Laplace. By the end of this chapter, the reader should be able to write Python code for morphological image processing (for example, opening, closing, skeletonizing, and computing the convex hull).