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OpenCV By Example

You're reading from  OpenCV By Example

Product type Book
Published in Jan 2016
Publisher Packt
ISBN-13 9781785280948
Pages 296 pages
Edition 1st Edition
Languages
Authors (3):
Prateek Joshi Prateek Joshi
Profile icon Prateek Joshi
David Millán Escrivá David Millán Escrivá
Profile icon David Millán Escrivá
Vinícius G. Mendonça Vinícius G. Mendonça
Profile icon Vinícius G. Mendonça
View More author details

Table of Contents (18) Chapters

OpenCV By Example
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Getting Started with OpenCV 2. An Introduction to the Basics of OpenCV 3. Learning the Graphical User Interface and Basic Filtering 4. Delving into Histograms 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 Index

Segmenting our input image


Now, we will introduce you to the following two techniques used to segment our thresholded image:

  • The connected components

  • The findContours function

With these two techniques, we will be allowed to extract each region of interest of our image where our target objects appear; in our case, a nut, screw, and ring.

The connected component algorithm

The connected component is a very common algorithm used to segment and identify parts in binary images. A connected component is an iterative algorithm used for the purpose of labeling an image using an 8- or 4-connectivity pixel. Two pixels are connected if they have the same value and are neighbors. In the following figure, each pixel has eight neighbor pixels:

A 4-connectivity means that only the 2, 4, 5, and 7 neighbors can be connected to the center if they have the same value. In the case of 8-connectivity, 1, 2, 3, 4, 5, 6, 7, and 8 can be connected if they have the same value.

In the following example, we can see the difference...

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