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OpenCV Computer Vision with Java

You're reading from   OpenCV Computer Vision with Java Create multiplatform computer vision desktop and web applications using the combination of OpenCV and Java

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Product type Paperback
Published in Jul 2015
Publisher
ISBN-13 9781783283972
Length 174 pages
Edition 1st Edition
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Author (1):
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Daniel Lelis Baggio Daniel Lelis Baggio
Author Profile Icon Daniel Lelis Baggio
Daniel Lelis Baggio
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Toc

Table of Contents (9) Chapters Close

Preface 1. Setting Up OpenCV for Java FREE CHAPTER 2. Handling Matrices, Files, Cameras, and GUIs 3. Image Filters and Morphological Operators 4. Image Transforms 5. Object Detection Using Ada Boost and Haar Cascades 6. Detecting Foreground and Background Regions and Depth with a Kinect Device 7. OpenCV on the Server Side Index

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...

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