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Home > Data > Computer Vision > OpenCV Computer Vision with Java
OpenCV Computer Vision with Java
OpenCV Computer Vision with Java

OpenCV Computer Vision with Java: Create multiplatform computer vision desktop and web applications using the combination of OpenCV and Java

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OpenCV Computer Vision with Java

Chapter 2. Handling Matrices, Files, Cameras, and GUIs

This chapter will enable you to perform basic operations required in computer vision, such as dealing with matrices, opening files, capturing videos from a camera, playing videos, and creating GUIs for prototype applications.

In this chapter, the following topics will be covered:

  • Basic matrix manipulation
  • Pixel manipulation
  • How to load and display images from files
  • How to capture a video from a camera
  • Video playback
  • Swing GUI's integration with OpenCV

By the end of this chapter, you should be able to get this computer vision application started by loading images and creating nice GUIs to manipulate them.

Basic matrix manipulation

From a computer vision background, we can see an image as a matrix of numerical values, which represents its pixels. For a gray-level image, we usually assign values ranging from 0 (black) to 255 (white) and the numbers in between show a mixture of both. These are generally 8-bit images. So, each element of the matrix refers to each pixel on the gray-level image, the number of columns refers to the image width, as well as the number of rows refers to the image's height. In order to represent a color image, we usually adopt each pixel as a combination of three basic colors: red, green, and blue. So, each pixel in the matrix is represented by a triplet of colors.

Note

It is important to observe that with 8 bits, we get 2 to the power of eight (28), which is 256. So, we can represent the range from 0 to 255, which includes, respectively the values used for black and white levels in 8-bit grayscale images. Besides this, we can also represent these levels as floating...

Pixel manipulation

Pixel manipulation is often required for one to access pixels in an image. There are several ways to do this and each one has its advantages and disadvantages. A straightforward method to do this is the put(row, col, value) method. For instance, in order to fill our preceding matrix with values {1, 2, 3}, we will use the following code:

for(int i=0;i<image.rows();i++){
  for(int j=0;j<image.cols();j++){ 
    image.put(i, j, new byte[]{1,2,3});
  }
}

Tip

Note that in the array of bytes {1, 2, 3}, for our matrix, 1 stands for the blue channel, 2 for the green, and 3 for the red channel, as OpenCV stores its matrix internally in the BGR (blue, green, and red) format.

It is okay to access pixels this way for small matrices. The only problem is the overhead of JNI calls for big images. Remember that even a small 640 x 480 pixel image has 307,200 pixels and if we think about a colored image, it has 921,600 values in a matrix. Imagine that it might take around 50ms to make...

Loading and displaying images from files

Most computer vision applications need to retrieve images from some where. In case you need to get them from files, OpenCV comes with several image file loaders. Unfortunately, some loaders depend on codecs that sometimes aren't shipped with the operating system, which might cause them not to load. From the documentation, we see that the following files are supported with some caveats:

  • Windows bitmaps: *.bmp, *.dib
  • JPEG files: *.jpeg, *.jpg, *.jpe
  • JPEG 2000 files: *.jp2
  • Portable Network Graphics: *.png
  • Portable image format: *.pbm, *.pgm, *.ppm
  • Sun rasters: *.sr, *.ras
  • TIFF files: *.tiff, *.tif

Note that Windows bitmaps, the portable image format, and sun raster formats are supported by all platforms, but the other formats depend on a few details. In Microsoft Windows and Mac OS X, OpenCV can always read the jpeg, png, and tiff formats. In Linux, OpenCV will look for codecs supplied with the OS, as stated by the documentation, so remember to install...

Displaying an image with Swing

OpenCV developers are used to a simple cross-platform GUI by OpenCV, which was called as HighGUI, and a handy method called imshow. It constructs a window easily and displays an image within it, which is nice to create quick prototypes. As Java comes with a popular GUI API called Swing, we had better use it. Besides, no imshow method was available for Java until its 2.4.7.0 version was released. On the other hand, it is pretty simple to create such functionality. Refer to the reference code in chapter2/swing-imageshow.

Let's break down the work in to two classes: App and ImageViewer. The App class will be responsible for loading the file, while ImageViewer will display it. The application's work is simple and will only need to use Imgcodecs's imread method, which is shown as follows:

package org.javaopencvbook;

import java.io.File;
…
import org.opencv.imgcodecs.Imgcodecs;

public class App
{
  static{ System.loadLibrary(Core.NATIVE_LIBRARY_NAME...

Capturing a video from a camera

The process of capturing frames from a webcam is very complex and it involves hardware details as well as heavy decoding or decompression algorithms. Fortunately, OpenCV has wrapped it all in a simple, yet powerful class called VideoCapture. This class not only grabs an image from a webcam, but also reads video files. In case more advanced access to a camera is required, you may want to use its specialized drivers.

You can think of a video stream as a series of pictures and you can retrieve each image in Mat and process it as you like. In order to use the VideoCapture class to capture a webcam stream, you need to instantiate it using the VideoCapture(int device) constructor. Note that the constructor parameter refers to the camera index in case you have several cameras. So, if you have one built-in camera and one USB camera and you create a videocapture object, such as new VideoCapture(1), then this object will refer to your built-in camera, while new VideoCapture...

Basic matrix manipulation

From a computer vision background, we can see an image as a matrix of numerical values, which represents its pixels. For a gray-level image, we usually assign values ranging from 0 (black) to 255 (white) and the numbers in between show a mixture of both. These are generally 8-bit images. So, each element of the matrix refers to each pixel on the gray-level image, the number of columns refers to the image width, as well as the number of rows refers to the image's height. In order to represent a color image, we usually adopt each pixel as a combination of three basic colors: red, green, and blue. So, each pixel in the matrix is represented by a triplet of colors.

Note

It is important to observe that with 8 bits, we get 2 to the power of eight (28), which is 256. So, we can represent the range from 0 to 255, which includes, respectively the values used for black and white levels in 8-bit grayscale images. Besides this, we can also represent these levels as floating points...

Pixel manipulation

Pixel manipulation is often required for one to access pixels in an image. There are several ways to do this and each one has its advantages and disadvantages. A straightforward method to do this is the put(row, col, value) method. For instance, in order to fill our preceding matrix with values {1, 2, 3}, we will use the following code:

for(int i=0;i<image.rows();i++){
  for(int j=0;j<image.cols();j++){ 
    image.put(i, j, new byte[]{1,2,3});
  }
}

Tip

Note that in the array of bytes {1, 2, 3}, for our matrix, 1 stands for the blue channel, 2 for the green, and 3 for the red channel, as OpenCV stores its matrix internally in the BGR (blue, green, and red) format.

It is okay to access pixels this way for small matrices. The only problem is the overhead of JNI calls for big images. Remember that even a small 640 x 480 pixel image has 307,200 pixels and if we think about a colored image, it has 921,600 values in a matrix. Imagine that it might take around 50ms to make...

Loading and displaying images from files

Most computer vision applications need to retrieve images from some where. In case you need to get them from files, OpenCV comes with several image file loaders. Unfortunately, some loaders depend on codecs that sometimes aren't shipped with the operating system, which might cause them not to load. From the documentation, we see that the following files are supported with some caveats:

  • Windows bitmaps: *.bmp, *.dib

  • JPEG files: *.jpeg, *.jpg, *.jpe

  • JPEG 2000 files: *.jp2

  • Portable Network Graphics: *.png

  • Portable image format: *.pbm, *.pgm, *.ppm

  • Sun rasters: *.sr, *.ras

  • TIFF files: *.tiff, *.tif

Note that Windows bitmaps, the portable image format, and sun raster formats are supported by all platforms, but the other formats depend on a few details. In Microsoft Windows and Mac OS X, OpenCV can always read the jpeg, png, and tiff formats. In Linux, OpenCV will look for codecs supplied with the OS, as stated by the documentation, so remember to install the relevant...

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Description

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.

Who is this book 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.

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

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 30, 2015
Length: 174 pages
Edition : 1st
Language : English
ISBN-13 : 9781783283989
Vendor :
Intel
Category :
Data
Languages :
Java
Concepts :
Computer Vision
Tools :
OpenCV

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Publication date : Jul 30, 2015
Length: 174 pages
Edition : 1st
Language : English
ISBN-13 : 9781783283989
Vendor :
Intel
Category :
Data
Languages :
Java
Concepts :
Computer Vision
Tools :
OpenCV

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Table of Contents

8 Chapters
1. Setting Up OpenCV for Java Chevron down icon Chevron up icon
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
Summary
2. Handling Matrices, Files, Cameras, and GUIs Chevron down icon Chevron up icon
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 Chevron down icon Chevron up icon
3. Image Filters and Morphological Operators
Smoothing
Morphological operators
Flood filling
Image pyramids
Thresholding
Summary
4. Image Transforms Chevron down icon Chevron up icon
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 Chevron down icon Chevron up icon
5. Object Detection Using Ada Boost and Haar Cascades
The boosting theory
Cascade classifier detection and training
Detection
Training
References
Summary
6. Detecting Foreground and Background Regions and Depth with a Kinect Device Chevron down icon Chevron up icon
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
Summary
7. OpenCV on the Server Side Chevron down icon Chevron up icon
7. OpenCV on the Server Side
Setting up an OpenCV web application
Mixed reality web applications
Image processing
Summary
Index Chevron down icon Chevron up icon
Index

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Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.4
(5 Ratings)
5 star 20%
4 star 40%
3 star 20%
2 star 0%
1 star 20%
splendkryp May 31, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Very simple examples and great to start developing with OpenCV
Amazon Verified review Amazon
dreamgast-little Mar 29, 2016
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
My problems with OpenCV were related to the installation of jdk8.0 and to make opencv compile and run on linux. Once installed you need to know about ant, eclipse, netbeans or maven.No easy for beginners but with internet and time.... Once the difficult installation done, you can find most informations on the site opencv.org.Why then 4 stars: This book is a good start for java opencv but not enough information are given about the installation and the reader is left alone to find links in internet for additional help
Amazon Verified review Amazon
CorGai Sep 24, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Das Buch beginnt sehr gut brauchbar, auch für Anfänger: Installation von OpenCV unter Eclipse, NetBeans..... Auch das erste Fallbeispiel, ein einfacher Grafik-Filter, ist noch sehr ausführlich erklärt. Danach wird das Buch schnell anspruchsvoller. Für mich - Java-Anfänger - ist das Buch dennoch insgesamt recht gut, weil viele verschiedene Methoden von OpenCV und Swing dargestellt werden. Macht Appetit nach mehr! Ich pesönlich möchte mich in Richtung Objekterkennung weiter entwickeln. Hierzu sind einige wenige Methoden beschrieben. Wer "nur" anwenden will, findet sicher Gefallen an der Begleitsoftware, die von der Verleger-Seite herunter geladen werden kann.
Amazon Verified review Amazon
Amazon Customer Apr 09, 2017
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
some of the codes in the book are incomplete and you already need to understand java coding to use that book.
Amazon Verified review Amazon
OLFO79 Nov 25, 2016
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
A book dealing with a software library should give an overview over the library like structure, classes,.. I did not find anything like that in the book. It's just a collection of short examples.There are many mistakes in the sample code:The Java-Wrapper has switched rows and columns compared to C++, so you always get only one line from the Hough-Transformation, if you look on the cols instead of the rows of the result. The Canny-Function does not accept aperture > 7, and so on....If you know Java, you will not learn much about Computer Vision from this book. If you know Computer Vision you will not learn much about Java. There's just a lot of source code to fill the pages..
Amazon Verified review Amazon

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About the author

Profile icon Baggio
Baggio
Daniel Lélis Baggio has started his works in computer vision through medical image processing at InCor (Instituto do Coração – Heart Institute) in São Paulo, Brazil, where he worked with intra-vascular ultrasound (IVUS) image segmentation. After that he has focused on GPGPU and ported that algorithm to work with NVidia's Cuda. He has also dived into 6 degrees of freedom head tracking with Natural User Interface group through a project called EHCI (http://code.google.com/p/ehci/ ). He also wrote “Mastering OpenCV with Practical Computer Vision Projects” from Packt Publishing.
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  • To contact us directly if a problem is not resolved, use www.packtpub.com/contact-us
What eBook formats do Packt support? Chevron down icon Chevron up icon

Our eBooks are currently available in a variety of formats such as PDF and ePubs. In the future, this may well change with trends and development in technology, but please note that our PDFs are not Adobe eBook Reader format, which has greater restrictions on security.

You will need to use Adobe Reader v9 or later in order to read Packt's PDF eBooks.

What are the benefits of eBooks? Chevron down icon Chevron up icon
  • You can get the information you need immediately
  • You can easily take them with you on a laptop
  • You can download them an unlimited number of times
  • You can print them out
  • They are copy-paste enabled
  • They are searchable
  • There is no password protection
  • They are lower price than print
  • They save resources and space
What is an eBook? Chevron down icon Chevron up icon

Packt eBooks are a complete electronic version of the print edition, available in PDF and ePub formats. Every piece of content down to the page numbering is the same. Because we save the costs of printing and shipping the book to you, we are able to offer eBooks at a lower cost than print editions.

When you have purchased an eBook, simply login to your account and click on the link in Your Download Area. We recommend you saving the file to your hard drive before opening it.

For optimal viewing of our eBooks, we recommend you download and install the free Adobe Reader version 9.