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OpenCV By Example

OpenCV By Example

By : Joshi, Millán Escrivá, Vinícius G. Mendonça
3.8 (5)
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OpenCV By Example

OpenCV By Example

3.8 (5)
By: Joshi, Millán Escrivá, Vinícius G. Mendonça

Overview of this book

Open CV is a cross-platform, free-for-use library that is primarily used for real-time Computer Vision and image processing. It is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation. Whether you are completely new to the concept of Computer Vision or have a basic understanding of it, this book will be your guide to understanding the basic OpenCV concepts and algorithms through amazing real-world examples and projects. Starting from the installation of OpenCV on your system and understanding the basics of image processing, we swiftly move on to creating optical flow video analysis or text recognition in complex scenes, and will take you through the commonly used Computer Vision techniques to build your own Open CV projects from scratch. By the end of this book, you will be familiar with the basics of Open CV such as matrix operations, filters, and histograms, as well as more advanced concepts such as segmentation, machine learning, complex video analysis, and text recognition.
Table of Contents (13 chapters)
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12
Index

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

In the previous chapter, we learned about histograms and filters that allowed us to understand image manipulation and create a photo application.

In this chapter, we will introduce you to the basic concepts of object segmentation and detection, which means isolation the objects that appear in an image for future processing and analysis.

In this chapter, we will cover the following topics:

  • Noise removal
  • The basics of light/background removal
  • The thresholding operation
  • A connected component for object segmentation
  • Finding contours for object segmentation

The industry sector uses complex Computer Vision systems and hardware. Computer Vision tries to detect the problems and minimizes errors produced in the production process and increases the quality of final products.

In this sector, the name for Computer Vision tasks is Automated Optical Inspection or AOI. This name appears in the inspection of printed circuit board...

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