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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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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

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...

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