Chapter 1, I/O and GUI, teaches the basic operations with images and video: loading, saving and displaying.
Chapter 2, Matrices, Colors, and Filters, covers operations to manipulate with matrices: accessing regions of an image, channels, and pixels. Conversions between various color spaces and usage of filters are also described.
Chapter 3, Contours and Segmentation, shows how to create image masks, find contours, and segment images.
Chapter 4, Object Detection and Machine Learning, describes ways of detecting and tracking different types of objects, from specially constructed (QR codes and ArUCo markers) to ones that can be met in natural scenes.
Chapter 5, Deep Learning, outlines new functionality in OpenCV connected with Deep Neural Nets. It provides examples of loading Deep Learning models and applying them to Computer Vision tasks.
Chapter 6, Linear Algebra, dives into useful mathematical methods for solving linear algebra problems and provides examples of applying these methods in Computer Vision.
Chapter 7, Detectors and Descriptors, contains information about how to work with image feature descriptors: how to compute them with different methods, how to display them, and how to match them for object detection and tracking purposes.
Chapter 8, Image and Video Processing, shows readers how to work with image sequences and get results based on correlations among the sequence.
Chapter 9, Multiple View Geometry, describes how to use cameras to retrieve information about 3D geometry of the scene.