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

The cartoonize effect

In the last section of this chapter, we create another effect called cartoonize. The purpose of this effect is to create an image that looks like a cartoon. To do this, we divide the algorithm into two steps: edge detection and color filtering.

The cartoonCallback functions define this effect with the following code:

void cartoonCallback(int state, void* userData)
    /** EDGES **/
    // Apply median filter to remove possible noise
    Mat imgMedian;
    medianBlur(img, imgMedian, 7);

    // Detect edges with canny
    Mat imgCanny;
    Canny(imgMedian, imgCanny, 50, 150);
    // Dilate the edges
    Mat kernel= getStructuringElement(MORPH_RECT, Size(2,2));
    dilate(imgCanny, imgCanny, kernel);

    // Scale edges values to 1 and invert values
    imgCanny= imgCanny/255;
    imgCanny= 1-imgCanny;
    // Use float values to allow multiply between 0 and 1
    Mat imgCannyf;
    imgCanny.convertTo(imgCannyf, CV_32FC3);

    // Blur the edgest to do smooth...