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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
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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

A sample application – tattoo forensics

Let's conclude this chapter with a real-life (or perhaps fantasy-life) example. Imagine you are working for the Gotham forensics department and you need to identify a tattoo. You have the original picture of a criminal's tattoo (perhaps captured in CCTV footage), but you don't know the identity of the person. However, you possess a database of tattoos, indexed with the name of the person that the tattoo belongs to.

Let's divide this task into two parts:

  • Build a database by saving image descriptors to files
  • Load the database and scan for matches between a query image's descriptors and the descriptors in the database

We will cover these tasks in the next two subsections.

Saving image descriptors to file

The first thing we will do is save the image descriptors to an external file. This way, we don't have to recreate the descriptors every time we want to scan two images for matches.

For the purposes of our example...

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