Book Image

OpenCV By Example

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

OpenCV By Example

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 (18 chapters)
OpenCV By Example
About the Authors
About the Reviewers

Preprocessing the input image

This section introduces you to some of the most common techniques that can be applied to preprocess images in the context of object segmentation/detection. The preprocess is the first change that we make in a new image before we start with our work and extract the information that we require from it.

Normally, in the preprocessing step, we try to minimize the image noise, light conditions, or image deformations due to the camera lens. These steps minimize the errors when you try to detect objects or segment our image.

Noise removal

If we don't remove the noise, we can detect more objects than we expect because normally noise is represented as a small point in the image and can be segmented as an object. The sensor and scanner circuit normally produce this noise. This variation of brightness or color can be represented in different types, such as Gaussian noise, spike noise, and shot noise. There are different techniques that can be used to remove the noise. We...