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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

Detecting points using the Harris corner detector


Corner detection is a technique used to detect interest points in the image. These interest points are also called feature points or simply features in Computer Vision terminology. A corner is basically an intersection of two edges. An interest point is basically something that can be uniquely detected in an image. A corner is a particular case of an interest point. These interest points help us characterize an image. These points are used extensively in applications, such as object tracking, image classification, visual search, and so on. Since we know that the corners are interesting, let's see how we can detect them.

In Computer Vision, there is a popular corner detection technique called the Harris corner detector. We construct a 2 x 2 matrix based on partial derivatives of the grayscale image, and then analyze the eigenvalues. Now what does this mean? Well, let's dissect it so that we can understand it better. Let's consider a small...

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