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首页利用OpenCV 3.0 Java开发计算机视觉实战教程
"OpenCV 3.0 Computer Vision with Java(PACKT,2015)是一本实践教程,专为那些希望利用Java进行计算机视觉开发的读者设计。本书旨在教授如何在Java环境中配置和使用OpenCV 3.0,重点讲解基础图像处理任务,如滤波、图像变换等操作。作者Daniel Lélis Baggio引导读者通过实际项目,掌握如何运用Haar级联分类器进行人脸追踪,以及如何借助Kinect设备检测前景和背景区域。书中还深入探讨了服务器端OpenCV的应用,让开发者理解计算机视觉的核心原理,并能够快速扩展或自定义项目以满足个性化需求。 本书结构清晰,每章都配备可直接使用的项目,这些项目涵盖了许多实用的类,使得学习者能够在实践中加深对计算机视觉技术的理解。每个项目的功能都是由一系列精心设计的Java代码实现,确保了跨平台兼容性,适用于桌面和Web应用程序的开发。然而,读者需注意,本书提供的信息未经许可不得复制或传播,以保护版权。 尽管作者和Packt Publishing已经尽力确保信息的准确性,但书中的内容不带任何形式的保证,包括明示或暗示的质量保证。作者、出版社及其经销商不对因本书导致的直接或间接损失承担责任。此外,尽管作者在提及商标时已尽可能准确使用大写,但Packt Publishing无法确保所有提及的公司和产品名称的准确性,因为商标信息可能会随时间而变化。这是一本实用且深入的OpenCV与Java结合的计算机视觉指南,对于希望在这个领域深入学习和实践的开发者来说,是不可或缺的参考资料。"
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Table of Contents
[ iii ]
Chapter 7: OpenCV on the Server Side 127
Setting up an OpenCV web application 127
Creating a Maven-based web application 128
Adding OpenCV dependencies 130
Running the web application 132
Importing the project to Eclipse 133
Mixed reality web applications 135
Image upload 136
Image processing 139
The response image 141
Summary 142
Index 145
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[ v ]
Preface
Living in times when self-driving vehicles are becoming a reality might trigger
curious minds as to how could computers' incipient vision works. Having a face
recognized for access control, getting our pictures automatically organized by a
subject or person, and having characters automatically recognized from paper scans
are tasks that have become common in our lives. All these aforementioned actions
have been enlisted in the so-called study area of computer vision.
As a scientic discipline, the theory behind systems that can extract information
from images can be described as computer vision, and it has been adopted to extract
valuable measurements from medical images, as well as to help humans delineate
the boundaries of important image areas in the so-called semi-automatic procedures.
In the context of providing a simple-to-use computer vision infrastructure to help
people rapidly build sophisticated vision applications, an open source library was
created: OpenCV. It was designed for real-time applications and is written in C++,
containing several hundred computer vision algorithms.
Although OpenCV had its debut alpha release back in January 1999, it was only in
February 2013 that it ofcially supported desktop Java through bindings. As this
is one of the most popular introductory teaching languages adopted in computer
science departments as well as K-12 computer-related courses, it is important to
have a good reference for how to build vision apps in a Java environment.
This book covers the basic OpenCV computer vision algorithms and their integration
with Java. As the Swing GUI widget toolkit is widely adopted to build GUIs in
Java, in this book, you will benet from the chapters that deal with this topic as
well as come to know how to set up your development environment that deals with
native code bindings. Besides, operations such as stretching, shrinking, warping,
and rotating, as well as nding edges, lines, and circles are all covered through
interesting and practical sample projects in this book.
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Preface
[ vi ]
As the Kinect device has become a great tool for background segmentation, we have
covered it in this chapter as well.
Another hot topic that is commonly explored with computer vision is machine
learning, and in this book, you will nd useful information to create your own object
tracker and to use OpenCV's built-in face tracker as well.
Since Java has been widely used for web applications, we have covered computer
vision applications on the server side as well, explaining the details of image
uploading and integration with OpenCV.
By the end of this book, you will have a solid background in how to use Java with
OpenCV from setup to server side; a brief explanation of the basic computer vision
topics are covered in the book. Also, you'll get the source code of several complete
projects from which you can extend and add your own functionality.
What this book covers
Chapter 1, Setting Up OpenCV for Java, covers the setting up of a library and
development environment. This chapter covers Eclipse and NetBeans IDEs,
as well as explaining the Ant and Maven build tools conguration.
Chapter 2, Handling Matrices, Files, Cameras, and GUIs, shows how to access matrices at
the pixel level as well as how to load and display images from les and web cameras.
It also covers the Swing widget toolkit support and how to work with OpenCV.
Chapter 3, Image Filters and Morphological Operators, deals with the process of
removing noise from images as well as morphological operators. It also explains
image pyramids and topics such as ood ll and image thresholding.
Chapter 4, Image Transforms, explains important transformations to nd edges,
such as the Gradient and Sobel lters. Additionally, it also explains line and circle
Hough transforms, which are used to identify not only straight but also radial lines.
The Discrete Fourier analysis and some distance transforms are also explained in
this chapter.
Chapter 5, Object Detection Using Ada Boost and Haar Cascades, demonstrates how to
create your own classier to nd some objects, as well as how to use the famous
face detection classier.
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Preface
[ vii ]
Chapter 6, Detecting Foreground and Background Regions and Depth with a Kinect Device,
explores the important problem of extracting your background. Furthermore, it
explains how to use a Kinect device to retrieve depth information.
Chapter 7, OpenCV on the Server Side, explains how to set up a web server application
with OpenCV.
What you need for 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 nd 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.
Who this book is for
If you are a C/C++ 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
nd this book very useful to migrate your applications to Java.
All you need is a basic knowledge of Java. No prior understanding of computer
vision is required, as this book will give you clear explanations and examples of
the basics.
Conventions
In this book, you will nd a number of text styles that distinguish between different
kinds of information. Here are some examples of these styles and an explanation of
their meaning.
Code words in text, database table names, folder names, lenames, le extensions,
pathnames, dummy URLs, user input, and Twitter handles are shown as follows:
"Another way to get the source code is by using the
git tool."
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