OpenCV, arguably the most widely used computer vision library, includes hundreds of ready-to-use imaging and vision functions and is extensively used in both academia and industry. As cameras get cheaper and imaging features grow in demand, the range of applications taking advantage of OpenCV is increasing significantly, particularly for mobile platforms.
As a computer vision library, OpenCV provides the following two big advantages:
- It is open source and everyone can freely use it, either on an academic level or for real-life projects
- It arguably contains the most extensive and up-to-date collection of computer vision functions
OpenCV is fed with cutting-edge research in Computer Vision, image and video processing, and machine learning.
The first book published on OpenCV provided a mostly theoretical approach, explaining the underlying computer vision techniques. Subsequent books have adopted the contrary approach, filling pages and pages with large examples (almost complete applications) that are difficult to follow. Large examples are difficult to follow and cannot be easily reused in the reader's projects. Examples taking up several pages are simply not appropriate for a book. We believe that examples should be easy to understand and should also be used as building blocks to reduce the time needed to have a working example for the reader's projects. Consequently, in this book, we also adopt a practical approach, although we aim to cover a larger spectrum of functions with shorter, easy-to-follow examples. From our experience with OpenCV, we can affirm that examples are ultimately the most valuable resource.
Chapter 1, Getting Started, deals with the basic installation steps and introduces the essential concepts of the OpenCV API. The first examples to read/write images and video and capture them from a camera are also provided.
Chapter 2, Something We Look At – Graphical User Interfaces, covers user interface capabilities for our OpenCV-based applications.
Chapter 3, First Things First – Image Processing, covers the most useful image processing techniques available in OpenCV.
Chapter 4, What's in the Image? Segmentation, tackles the all-important problem of image segmentation in OpenCV.
Chapter 5, Focusing on the Interesting 2D Features, covers the functions available for extracting keypoints and descriptors from an image.
Chapter 6, Where's Wally? Object Detection, describes that object detection is a central problem in computer vision. This chapter explains the functionality available for object detection.
Chapter 7, What Is He Doing? Motion, considers more than just a single static image. This chapter deals with motion and tracking in OpenCV.
Chapter 8, Advanced Topics, focuses on some advanced topics such as machine learning and GPU-based acceleration.