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OpenCV Computer Vision with Java

OpenCV Computer Vision with Java

By : Baggio
3.4 (5)
Buy this Book
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OpenCV Computer Vision with Java

OpenCV Computer Vision with Java

3.4 (5)
By: Baggio
Buy this Book

Overview of this book

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.
Table of Contents (9 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Setting Up OpenCV for Java
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1. Setting Up OpenCV for Java
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Getting OpenCV for Java development
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Building OpenCV from the source code
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The Java OpenCV project in Eclipse
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The NetBeans configuration
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A Java OpenCV simple application
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Building your project with Ant
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The Java OpenCV Maven configuration
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Summary
2
2. Handling Matrices, Files, Cameras, and GUIs
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2. Handling Matrices, Files, Cameras, and GUIs
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Basic matrix manipulation
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Pixel manipulation
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Loading and displaying images from files
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Displaying an image with Swing
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Capturing a video from a camera
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Video playback
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Swing GUI's integration with OpenCV
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Summary
3
3. Image Filters and Morphological Operators
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3. Image Filters and Morphological Operators
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Smoothing
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Morphological operators
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Flood filling
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Image pyramids
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Thresholding
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Summary
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4. Image Transforms
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4. Image Transforms
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The Gradient and Sobel derivatives
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The Laplace and Canny transforms
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The line and circle Hough transforms
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Geometric transforms – stretch, shrink, warp, and rotate
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Discrete Fourier Transform and Discrete Cosine Transform
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Integral images
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Distance transforms
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Histogram equalization
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References
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Summary
5
5. Object Detection Using Ada Boost and Haar Cascades
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5. Object Detection Using Ada Boost and Haar Cascades
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The boosting theory
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Cascade classifier detection and training
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Detection
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Training
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References
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Summary
6
6. Detecting Foreground and Background Regions and Depth with a Kinect Device
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6. Detecting Foreground and Background Regions and Depth with a Kinect Device
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Background subtraction
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Frame differencing
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Averaging a background method
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The mixture of Gaussians method
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Contour finding
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Kinect depth maps
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Summary
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7. OpenCV on the Server Side
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7. OpenCV on the Server Side
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Setting up an OpenCV web application
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Mixed reality web applications
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Image processing
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Summary
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Index
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Index

Chapter 1. Setting Up OpenCV for Java

I'm sure you want to start developing astonishing computer vision applications. You must have heard of a nice C/C++ computer vision library called OpenCV to help you do so. But in case you would like to develop the applications using your knowledge of Java programming, we have good news for you. Since the release of OpenCV 2.4.4 in January 2013, Java bindings have been officially developed. So you can use them not only for desktop Java, but also for Scala development.

This chapter will set you up for OpenCV development right away. As Java developers are mostly used to working with tools such as Eclipse, NetBeans, Apache Ant, and Maven, we will cover the details of creating a simple OpenCV application using the environment that the Java developers are more used to.

In this chapter, we will do the following:

  • Get OpenCV with desktop Java support
  • Discuss Java Native Interface (JNI) details
  • Configure Eclipse and NetBeans for OpenCV
  • Create Apache Ant and Maven OpenCV projects

By the end of this chapter, the user should have an OpenCV for Java installation running on his OS which can easily be linked to Eclipse, NetBeans, Apache Ant, or Maven, the most used tools and building systems for Java.

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Programming languages
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OpenCV Computer Vision with Java
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