OpenCV 3.0 Computer Vision with Java

Daniel Lelis Baggio

• Publisher: Packt Publishing
• Year: 2015
• ISBN:
  9781783283989
• Edition: 1
• Topic: Computer Science
• Subtopic: Computer Vision & Pattern Recognition
• Index: Computer Science

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

Who This Book Is For

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

In Detail

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.

OpenCV 3.0 Computer Vision with Java

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Table of Contents

OpenCV 3.0 Computer Vision with Java

Credits

About the Author

Acknowledgment

About the Reviewers

www.PacktPub.com

Support files, eBooks, discount offers, and more

Why subscribe?

Free access for Packt account holders

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Downloading the color images of this book

Errata

Piracy

Questions

1. Setting Up OpenCV for Java

Getting OpenCV for Java development

Building OpenCV from the source code

The Java OpenCV project in Eclipse

The NetBeans configuration

A Java OpenCV simple application

Building your project with Ant

The Java OpenCV Maven configuration

Creating a Windows Java OpenCV Maven project pointing to the Packt repository

Creating a Java OpenCV Maven project pointing to a local repository

Summary

2. Handling Matrices, Files, Cameras, and GUIs

Basic matrix manipulation

Pixel manipulation

Loading and displaying images from files

Displaying an image with Swing

Capturing a video from a camera

Video playback

Swing GUI's integration with OpenCV

Summary

3. Image Filters and Morphological Operators

Smoothing

Averaging

Gaussian

Median filtering

Bilateral filtering

Morphological operators

Flood filling

Image pyramids

Thresholding

Summary

4. Image Transforms

The Gradient and Sobel derivatives

The Laplace and Canny transforms

The line and circle Hough transforms

Geometric transforms – stretch, shrink, warp, and rotate

Discrete Fourier Transform and Discrete Cosine Transform

Integral images

Distance transforms

Histogram equalization

References

Summary

5. Object Detection Using Ada Boost and Haar Cascades

The boosting theory

AdaBoost

Cascade classifier detection and training

Detection

Training

References

Summary

6. Detecting Foreground and Background Regions and Depth with a Kinect Device

Background subtraction

Frame differencing

Averaging a background method

The mixture of Gaussians method

Contour finding

Kinect depth maps

The Kinect setup

The driver setup

The OpenCV Kinect support

The Kinect depth application

Summary

7. OpenCV on the Server Side

Setting up an OpenCV web application

Creating a Maven-based web application

Adding OpenCV dependencies

Running the web application

Importing the project to Eclipse

Mixed reality web applications

Image upload

Image processing

The response image

Summary

Index

OpenCV 3.0 Computer Vision with Java

Copyright © 2015 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: July 2015

Production reference: 1270715

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78328-397-2

www.packtpub.com

Credits

Author

Daniel Lélis Baggio

Reviewers

Ngoc Dao

Dileep Kumar Kotha

Domenico Luciani

Sebastian Montabone

Commissioning Editor

Kunal Parikh

Acquisition Editor

Harsha Bharwani

Content Development Editor

Nikhil Potdukhe

Technical Editor

Parag Topre

Copy Editors

Sarang Chari

Sonia Mathur

Swati Priya

Neha Vyas

Project Coordinator

Judie Jose

Proofreader

Safis Editing

Indexer

Monica Ajmera Mehta

Graphics

Disha Haria

Production Coordinator

Arvindkumar Gupta

Cover Work

Arvindkumar Gupta

About the Author

Daniel Lélis Baggio started his work in computer vision through medical image processing at Instituto do Coração (InCor), which is a heart institute in São Paulo, Brazil, where he worked with intravascular ultrasound (IVUS) image segmentation. After this, he focused on GPGPU and ported that algorithm to work with NVIDIA's CUDA. He also dived into the topic of six degrees of freedom (6DoF), head tracking through a project called EHCI (http://code.google.com/p/ehci/) with the Natural User Interface group.

He is also the author of Mastering OpenCV with Practical Computer Vision Projects, Packt Publishing.

Acknowledgment

I'd first like to thank God for all the opportunities He has given me as well as for giving me our happy family.

I'd certainly like to thank Professor Sergio Furuie for introducing me to this wonderful world of computer vision. I'd also like to thank Professor Carlos Henrique Forster for his courses on the subject.

A big thanks goes to all the reviewers of this book, who took their time to put constructive and interesting corrections to its contents.

I would also like to thank the people from Packt Publishing—especially Parag Topre, Nikhil Potdukhe, Sriram Neelakantan, Harsha Bharwani, Sageer Parkar, and Nadeem Bagban—without whom, this book would never have been finished. I would also like to thank them for their patience.

I would like to thank my parents, who brought me into this world and educated me. I also thank my brother for always being there for me.

I dedicate this book to my children, who will always be part of my heart.

I'd also like to thank my wife for supporting me day and night in our life's journey.

About the Reviewers

Ngoc Dao studied computer vision at the Computer Vision and Image Media Lab of the University of Tsukuba, Japan. He has created several high-speed and scalable image matching server systems using Scala, Akka, and MongoDB with OpenCV's Java binding. These systems can scale multiple machines and have successfully been used with many iOS and Android apps.

Other than computer vision, Ngoc is also interested in real-time distributed systems and web frameworks. He is the main author of Xitrum, which is an open source async and clustered web framework for Scala (http://xitrum-framework.github.io). He presented this framework at the Scala Matsuri 2014 conference in Tokyo (http://scalamatsuri.org/en/program/index.html).

I would like to thank Professor Yuichi Ohta, Professor Yoshinari Kameda, and Professor Kitahara Itaru at the University of Tsukuba. They taught me a lot about computer vision.

Dileep Kumar Kotha currently works as a senior software engineer at a telecom firm in Bangalore, India. He is an undergraduate in computer science from the National Institute of Technology, Rourkela, 2012 batch. He started working on image processing during his summer internship at the presti...

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