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OpenCV By Example

OpenCV By Example

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

OpenCV By Example

3.8 (5)
By: Prateek Joshi, David 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

Automatic object inspection classification example


Continuing with the example of the previous chapter, the automatic object inspection segmentation, where a carrier tape contains three different types of objects (nuts, screws, and rings), and with Computer Vision, we will be able to recognize each one of them to send notifications to a robot or similar to put each one in different boxes.

In Chapter 5, Automated Optical Inspection, Object Segmentation, and Detection, we preprocessed the input images and extracted the regions of interest of images and isolated each object using different techniques. Now, we will apply all these concepts, as explained in previous sections, in this example to extract features and classify each object and allow to possible robot to put each one in different boxes. In our application, we are only going to show the labels of each image in an image, but we can send the positions in the image and the labels to other devices as a robot.

Then, our goal is from an input...

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OpenCV By Example
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