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Learning OpenCV 3 Computer Vision with Python (Update)

You're reading from   Learning OpenCV 3 Computer Vision with Python (Update) Unleash the power of computer vision with Python using OpenCV

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Product type Paperback
Published in Sep 2015
Publisher
ISBN-13 9781785283840
Length 266 pages
Edition 1st Edition
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Toc

Table of Contents (11) Chapters Close

Preface 1. Setting Up OpenCV FREE CHAPTER 2. Handling Files, Cameras, and GUIs 3. Processing Images with OpenCV 3 4. Depth Estimation and Segmentation 5. Detecting and Recognizing Faces 6. Retrieving Images and Searching Using Image Descriptors 7. Detecting and Recognizing Objects 8. Tracking Objects 9. Neural Networks with OpenCV – an Introduction Index

The Fourier Transform

Much of the processing you apply to images and videos in OpenCV involves the concept of Fourier Transform in some capacity. Joseph Fourier was an 18th century French mathematician who discovered and popularized many mathematical concepts, and concentrated his work on studying the laws governing heat, and in mathematics, all things waveform. In particular, he observed that all waveforms are just the sum of simple sinusoids of different frequencies.

In other words, the waveforms you observe all around you are the sum of other waveforms. This concept is incredibly useful when manipulating images, because it allows us to identify regions in images where a signal (such as image pixels) changes a lot, and regions where the change is less dramatic. We can then arbitrarily mark these regions as noise or regions of interests, background or foreground, and so on. These are the frequencies that make up the original image, and we have the power to separate them to make sense of...

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