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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 2. An Introduction to the Basics of OpenCV FREE CHAPTER 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

Segmenting our input image

Now, we are going to introduce two techniques to segment our threshold image:

  • Connected components
  • Find contours

With these two techniques, we are allowed to extract each region of interest (ROI) of our image where our targets objects appear. In our case, these are the nut, screw, and ring.

The connected components algorithm

The connected component algorithm is a very common algorithm that's used to segment and identify parts in binary images. The connected component is an iterative algorithm with the purpose of labeling an image using eight or four connectivity pixels. Two pixels are connected if they have the same value and are neighbors. In an image, each pixel has eight neighbor pixels...

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