About This Book
- Set up Java API for OpenCV to create popular Swing-based Graphical User Interfaces (GUIs)
- Process videos and images in real-time with closer to native performance
- Make use of rock solid Java web application development practices to create engaging augmented reality experience and work with depth images from a Kinect device
If you are a Java developer, student, researcher, or hobbyist wanting to create computer vision applications in Java then this book is for you. If you are an experienced C/C++ developer who is used to working with OpenCV, you will also find this book very useful for migrating your applications to Java.
All you need is basic knowledge of Java, with no prior understanding of computer vision required, as this book will give you clear explanations and examples of the basics.
What You Will Learn
- Create powerful GUIs for computer vision applications with panels, scroll panes, radio buttons, sliders, windows, and mouse interaction using the popular Swing GUI widget toolkit
- Stretch, shrink, warp, and rotate images, as well as apply image transforms to find edges, lines, and circles, and even use Discrete Fourier Transforms (DFT)
- Detect foreground or background regions and work with depth images with a Kinect device
- Learn how to add computer vision capabilities to rock solid Java web applications allowing you to upload photos and create astonishing effects
- Track faces and apply mixed reality effects such as adding virtual hats to uploaded photos
- Filter noisy images, work with morphological operators, use flood fill, and threshold the important regions of an image
- Open and process video streams from webcams or video files
OpenCV 3.0 Computer Vision with Java is a practical tutorial guide that explains fundamental tasks from computer vision while focusing on Java development. This book will teach you how to set up OpenCV for Java and handle matrices using the basic operations of image processing such as filtering and image transforms. It will also help you learn how to use Haar cascades for tracking faces and to detect foreground and background regions with the help of a Kinect device. It will even give you insights into server-side OpenCV. Each chapter is presented with several projects that are ready to use. The functionality of these projects is found in many classes that allow developers to understand computer vision principles and rapidly extend or customize the projects for their needs.