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Learn OpenCV 4 by Building Projects

You're reading from   Learn OpenCV 4 by Building Projects Build real-world computer vision and image processing applications with OpenCV and C++

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781789341225
Length 310 pages
Edition 2nd Edition
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Authors (3):
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David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
Vinícius G. Mendonça Vinícius G. Mendonça
Author Profile Icon Vinícius G. Mendonça
Vinícius G. Mendonça
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Table of Contents (14) Chapters Close

Preface 1. Getting Started with OpenCV FREE CHAPTER 2. An Introduction to the Basics of OpenCV 3. Learning Graphical User Interfaces 4. Delving into Histogram and Filters 5. Automated Optical Inspection, Object Segmentation, and Detection 6. Learning Object Classification 7. Detecting Face Parts and Overlaying Masks 8. Video Surveillance, Background Modeling, and Morphological Operations 9. Learning Object Tracking 10. Developing Segmentation Algorithms for Text Recognition 11. Text Recognition with Tesseract 12. Deep Learning with OpenCV 13. Other Books You May Enjoy

Preprocessing the input image

This section introduces some of the most common techniques that we can apply for preprocessing images in the context of object segmentation/detection. The preprocessing is the first change we make to a new image before we start working and extracting the information we require from it. Normally, in the preprocessing step, we try to minimize the image noise, light conditions, or image deformation due to a camera lens. These steps minimize errors while detecting objects or segments in our image.

Noise removal

If we don't remove the noise, we can detect more objects than we expect because noise is normally represented as small points in the image and can be segmented as an object. The sensor...

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