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)

Automatic object inspection classification example

In Chapter 5, Automated Optical Inspection, Object Segmentation, and Detection, we looked at an example of automatic object inspection segmentation where a carrier tape contained three different types of object: nuts, screws, and rings. With computer vision, we will be able to recognize each one of these so that we can send notifications to a robot or put each one in a different box. The following is a basic diagram of the carrier tape:

In Chapter 5, Automated Optical Inspection, Object Segmentation, and Detection, we pre-processed the input images and extracted the regions of interest, isolating each object using different techniques. Now, we are going to apply all the concepts we explained in the previous sections in this example to extract features and classify each object, allowing the robot to put each one in a different...