Active contours, morphological snakes, and GrabCut algorithms

In this section, we will discuss some more sophisticated segmentation algorithms and demonstrate them with scikit-image or python-opencv (cv2) library functions. We will start with segmentation using the active contours. 

Active contours

The active contour model (also known as snakes) is a framework that fits open or closed splines to lines or edges in an image. A snake is an energy-minimizing, deformable spline influenced by constraint, image, and internal forces. Hence, it works by minimizing an energy that is partially defined by the image and partially by the spline's shape, length, and smoothness. The constraint and image forces pull the snake toward object contours and internal forces resist the deformation. The algorithm accepts an initial snake (around the object of interest) and to fit the closed contour to the object of interest, it shrinks/expands. The minimization is done explicitly in the image energy and implicitly...