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-imageandpython-opencv)
