Chapter 1, Introduction to Computer Vision and Raspberry Pi, illustrates the concept of single-board computers, OpenCV, and Raspberry Pi. We will also learn how to set up Raspbian OS on Raspberry Pi.

Chapter 2, Preparing Raspberry Pi for Computer Vision, teaches us how to set up Raspberry Pi for demonstrations of computer vision.

Chapter 3, Introduction to Python Programming, introduces us to Python 3 programming. We will learn about libraries such as NumPy and Matplotlib. We will also demonstrate the use of a few programs with LEDs and push buttons in detail.

Chapter 4, Getting Started with Computer Vision, focuses on the basics of computer vision programming and interfacing various camera modules with Raspberry Pi. We will also learn how to work with images and the GUI in this chapter in detail.

Chapter 5, Basics of Image Processing, looks at basic operations on images, such as bitwise arithmetic and bitwise logical operations.

Chapter 6, Colorspaces, Transformations, and Thresholding, is where we will analyze the concept of basic segmentation and thresholding. We will learn about various geometric and perspective transformations. We will also learn about colorspaces and their application in detail.

Chapter 7, Let's Make Some Noise, explores the concept of filters and how to use low-pass filters to reduce noise in images. We will learn about concepts such as kernels and convolution in detail.

Chapter 8, High-Pass Filters and Feature Detection, goes into the aspects of detecting various features, such as lines, circles, edges, and corners, using high-pass filtering techniques.

Chapter 9, Image Restoration, Segmentation, and Depth Map, investigates restoring degraded and damaged images, segmenting with Python's implementation of the k-means and mean-shift algorithms, and estimating depth maps.

Chapter 10, Histograms, Contours, and Morphological Transformations, analyzes images with histograms, and we will learn how to enhance images by equalizing histograms. We will also dig deeper into contours and mathematical morphological operations.

Chapter 11, Real-Life Applications of Computer Vision, demonstrates applications in the real world with OpenCV, Python 3, and Raspberry Pi.

Chapter 12, Working with Mahotas and Jupyter, delves into the brief usage of another scientific image processing library known as Mahotas. We will also understand how to work with the Jupyter Notebook for Python 3 programming.

Chapter 13, Appendix, is a collection of assorted topics relating to Python, Raspberry Pi, and computer vision that did not fit in to earlier chapters.