Overview
- Set up OpenCV and an Android development environment on Windows, Mac, or Linux
- Capture and display real-time videos and still images
- Manipulate image data using OpenCV and Apache Commons Math
- Track objects and render 2D and 3D graphics on top of them
- Create a photo-capture and photo-sharing app that supports a variety of filters with a real-time preview feature
In Detail
Take a smartphone from your pocket, and within a few seconds, you can snap a photo, manipulate it, and share it with the world. You have just achieved mass production of image data. With a computer vision library such as OpenCV, you can analyze and transform copious amounts of image data in real time on a mobile device. The upshot to this is that you, as developers, can provide mobile users with many new kinds of images, constantly highlighting certain visual features that are of artistic or practical interest. Android is a convenient platform for such experiments because it uses a high-level language (Java), it provides standardized interfaces for sharing image data between applications, and it is mostly open source, so everyone can study its implementation.
Android Application Programming with OpenCV is a practical, hands-on guide that covers the fundamental tasks of computer vision—capturing, filtering, and analyzing images-with step-by-step instructions for writing both an application and reusable library classes.
Android Application Programming with OpenCV looks at OpenCV's Java bindings for Android and dispels mysteries such as which version of these bindings to use, how to integrate with standard Android functionality for layout, event handling, and data sharing, and how to integrate with OpenGL for rendering. By following the clear, concise, and modular examples provided in this book, you will develop an application that previews, captures, and shares photos with special effects based on color manipulation, edge detection, image tracking, and 3D rendering.Beneath the application layer, you will develop a small but extensible library that you can reuse in your future projects. This library will include filters for selectively modifying an image based on edge detection, 2D and 3D image trackers, and adapters to convert the Android system's camera specifications into OpenCV and OpenGL projection matrices. If you want a quick start in computer vision for Android, then this is the book for you.
By the end of Android Application Programming with OpenCV, you will have developed a computer vision application that integrates OpenCV, Android SDK, and OpenGL.
What you will learn from this book
- Install OpenCV and an Android development environment on Windows, Mac, or Linux
- Capture, display, and save images
- Make images accessible to other apps via Android's MediaStore and Intent classes
- Integrate OpenCV events and views with Android's standard activity lifecycle and view hierarchy
- Learn how OpenCV uses matrices to store data about images, recognizable features in images, and camera characteristics
- Apply curves and other color transformations to simulate the look of old photos, movies, or video games
- Apply convolution filters that sharpen, blur, emboss, or darken edges and textures in an image
- Track real-world objects, especially printed images, in 2D and 3D space
- Extract camera data from Android SDK and use it to construct OpenCV and OpenGL projection matrices
- Render basic 3D graphics in OpenGL
Joseph Howse
Joseph (Joe) Howse might be at home right now, sitting on a sofa and writing a book, or he might have dashed away with a suitcase full of books, cameras, and computers. He is equipped to “see the world”, or at least to do his work in computer vision. He is currently a Software Developer at Ad-Dispatch (Canada), where he makes augmented reality games for iOS and Android. Thanks to computer vision, the games can make use of real-world props such as a child's drawings and toys.
Joe also provides training and consulting services. He is currently consulting at Market Beat (El Salvador) on an embedded systems project that uses OpenCV for face recognition. He holds three Master's degrees in Computer Science, International Development Studies, and Business Administration (Dalhousie University, Canada). His research has been published by ISMAR (the International Symposium on Mixed and Augmented Realities), and he would love to meet you there if you go.
Android Application Programming with OpenCV is Joe's second book with Packt. His first book, OpenCV: Computer Vision with Python, includes an introduction to face tracking and depth cameras (for example Kinect) on Windows, Mac, and Linux.
Joe likes cats, kittens, and oceans. Felines and saline water sustain him. He lives with his multi-species family in Halifax, on Canada's Atlantic coast.
