Chapter 8. Image Segmentation

In this chapter, we will discuss a key concept in image processing, namely segmentation. We will start by introducing the basic concepts of image segmentation and why it is so important. We will continue our discussion with a number of different image segmentation techniques along with their implementations in scikit-image and python-opencv(cv2) library functions.

 The topics to be covered in this chapter are as follows:

• Hough transform—circle and line detection in an image (with scikit-image)
• Thresholding and Otsu's segmentation (with scikit-image)
• Edges-based/region-based segmentation techniques (with scikit-image)
• Felzenszwalb, SLIC, QuickShift, and Compact Watershed algorithms (with scikit-image)
• Active contours, morphological snakes, and GrabCut algorithms (with scikit-image and python-opencv)