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Learning OpenCV 3 Application Development

You're reading from  Learning OpenCV 3 Application Development

Product type Book
Published in Dec 2016
Publisher Packt
ISBN-13 9781784391454
Pages 310 pages
Edition 1st Edition
Languages
Author (1):
Samyak Datta Samyak Datta
Profile icon Samyak Datta

Table of Contents (16) Chapters

Learning OpenCV 3 Application Development
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
1. Laying the Foundation 2. Image Filtering 3. Image Thresholding 4. Image Histograms 5. Image Derivatives and Edge Detection 6. Face Detection Using OpenCV 7. Affine Transformations and Face Alignment 8. Feature Descriptors in OpenCV 9. Machine Learning with OpenCV Command-line Arguments in C++

Color histograms in OpenCV


In this chapter so far, we have been working with grayscale images. Let's take a moment to understand the concept of histograms when applied to multichannel color images. For all demonstration purposes in this section, we will be working with the color version of Lena's picture as our input image:

While talking about the transition from grayscale to color images, we have always visualized color images as being composed of three channels of red, green, and blue. We have maintained that all three channels can be treated independently as grayscale images themselves. And this is exactly what we will do in the case of color histograms as well.

In the last few sections, we have seen how to compute as well as plot histograms for single-channel grayscale images. Now imagine performing the same operation across all the three channels of a color image to obtain three separate histograms. Since each individual channel is exactly the same as a grayscale image (all pixel intensities...

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