Book Image

Building Computer Vision Projects with OpenCV 4 and C++

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

Building Computer Vision Projects with OpenCV 4 and C++

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

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. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: •Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá •Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek Joshi
Table of Contents (28 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Chapter 5. Automated Optical Inspection, Object Segmentation, and Detection

In Chapter 4, Delving into Histogram and Filters, we learned about histograms and filters, which allow us to understand image manipulation and create a photo application.

In this chapter, we are going to introduce the basic concepts of object segmentation and detection. This means isolating the objects that appear in an image for future processing and analysis.

This chapter introduces the following topics:

  • Noise removal
  • Light/background removal basics
  • Thresholding
  • Connected components for object segmentation
  • Finding contours for object segmentation

Many industries use complex computer vision systems and hardware. Computer vision tries to detect problems and minimize errors produced in the production process, improving the quality of final products.

 

In this sector, the name for this computer vision task is Automated Optical Inspection (AOI). This name appears in the inspection of printed circuit board manufacturers, where...