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Mastering OpenCV 4 with Python

You're reading from  Mastering OpenCV 4 with Python

Product type Book
Published in Mar 2019
Publisher Packt
ISBN-13 9781789344912
Pages 532 pages
Edition 1st Edition
Languages
Author (1):
Alberto Fernández Villán Alberto Fernández Villán
Profile icon Alberto Fernández Villán

Table of Contents (20) Chapters

Preface 1. Section 1: Introduction to OpenCV 4 and Python
2. Setting Up OpenCV 3. Image Basics in OpenCV 4. Handling Files and Images 5. Constructing Basic Shapes in OpenCV 6. Section 2: Image Processing in OpenCV
7. Image Processing Techniques 8. Constructing and Building Histograms 9. Thresholding Techniques 10. Contour Detection, Filtering, and Drawing 11. Augmented Reality 12. Section 3: Machine Learning and Deep Learning in OpenCV
13. Machine Learning with OpenCV 14. Face Detection, Tracking, and Recognition 15. Introduction to Deep Learning 16. Section 4: Mobile and Web Computer Vision
17. Mobile and Web Computer Vision with Python and OpenCV 18. Assessments 19. Other Books You May Enjoy

Histogram comparison

One interesting functionality offered by OpenCV in connection with histograms is the cv2.compareHist() function, which can be used to get a numerical parameter expressing how well two histograms match each other. In this sense, as histograms reflect the intensity distributions of the pixel values in the image, this function can be used to compare images. As previously commented, the histograms show only statistical information and not the location of pixels. Therefore, a common approach for image comparison is to divide the image into a certain number of regions (commonly with the same size), calculate the histogram for each region, and, finally, concatenate all the histograms to create the feature representation of the image. In this example, for simplicity, we are not going to divide the image into a certain number of regions, so only one region (the full...

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