Book Image

Learn OpenCV 4 By Building Projects - Second Edition

By : David Millán Escrivá, Vinícius G. Mendonça, Prateek Joshi
Book Image

Learn OpenCV 4 By Building Projects - Second Edition

By: David Millán Escrivá, Vinícius G. Mendonça, Prateek Joshi

Overview of this book

OpenCV is one of the best open source libraries available, and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. Whether you’re completely new to computer vision, or have a basic understanding of its concepts, Learn OpenCV 4 by Building Projects – Second edition will be your guide to understanding OpenCV concepts and algorithms through real-world examples and projects. You’ll begin with the installation of OpenCV and the basics of image processing. Then, you’ll cover user interfaces and get deeper into image processing. As you progress through the book, you'll learn complex computer vision algorithms and explore machine learning and face detection. The book then guides you in creating optical flow video analysis and background subtraction in complex scenes. In the concluding chapters, you'll also learn about text segmentation and recognition and understand the basics of the new and improved deep learning module. By the end of this book, you'll be familiar with the basics of Open CV, such as matrix operations, filters, and histograms, and you'll have mastered commonly used computer vision techniques to build OpenCV projects from scratch.
Table of Contents (14 chapters)

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...