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Learning OpenCV 5 Computer Vision with Python

You're reading from   Learning OpenCV 5 Computer Vision with Python Tackle computer vision and machine learning with the newest tools, techniques and algorithms

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Product type Paperback
Published in Jul 2025
Publisher Packt
ISBN-13 9781803230221
Length
Edition 4th Edition
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Authors (2):
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Joe Minichino Joe Minichino
Author Profile Icon Joe Minichino
Joe Minichino
Joseph Howse Joseph Howse
Author Profile Icon Joseph Howse
Joseph Howse
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Table of Contents (12) Chapters Close

1. Learning OpenCV 5 Computer Vision with Python, Fourth Edition: Tackle tools, techniques, and algorithms for computer vision and machine learning FREE CHAPTER
2. Setting Up OpenCV 3. Handling Files, Cameras, and GUIs 4. Processing Images with OpenCV 5. Detecting and Recognizing Faces 6. Retrieving Images and Searching Using Image Descriptors 7. Building Custom Object Detectors 8. Tracking Objects 9. Camera Models and Augmented Reality 10. Introduction to Neural Networks with OpenCV 11. OpenCV Applications at Scale Appendix A: Bending Color Space with the Curves Filter

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Similar to the human eyes and brain, OpenCV can detect the main features of an image and extract them into so-called image descriptors. These features can then be used as a database, enabling image-based searches. Moreover, we can use key points to stitch images together and compose a bigger image. (Think of putting together many pictures to form a 360° panorama.)

This chapter will show you how to detect the features of an image with OpenCV and make use of them to match and search images. Over the course of this chapter, we will take sample images and detect their main features, and then try to find a region of another image that matches the sample image. We will also find the homography or spatial relationship between a sample image and a matching region of another image.

More specifically, we will cover the following tasks:

  • Detecting keypoints and extracting local descriptors around the keypoints using any of...
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