Book Image

OpenCV Computer Vision Application Programming Cookbook Second Edition

By : Robert Laganiere
Book Image

OpenCV Computer Vision Application Programming Cookbook Second Edition

By: Robert Laganiere

Overview of this book

OpenCV 3 Computer Vision Application Programming Cookbook is appropriate for novice C++ programmers who want to learn how to use the OpenCV library to build computer vision applications. It is also suitable for professional software developers wishing to be introduced to the concepts of computer vision programming. It can also be used as a companion book in a university-level computer vision courses. It constitutes an excellent reference for graduate students and researchers in image processing and computer vision.
Table of Contents (18 chapters)
OpenCV Computer Vision Application Programming Cookbook Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Fitting a line to a set of points


In some applications, it could be important to not only detect lines in an image, but also to obtain an accurate estimate of the line's position and orientation. This recipe will show you how to find the line that best fits a given set of points.

How to do it...

The first thing to do is to identify points in an image that seem to be aligned along a straight line. Let's use one of the lines we detected in the preceding recipe. The lines detected using cv::HoughLinesP are contained in std::vector<cv::Vec4i> called lines. To extract the set of points that seem to belong to, let's say, the first of these lines, we can proceed as follows. We draw a white line on a black image and intersect it with the Canny image of contours used to detect our lines. This is simply achieved by the following statements:

   int n=0; // we select line 0 
   // black image
   cv::Mat oneline(contours.size(),CV_8U,cv::Scalar(0));
   // white line
   cv::line(oneline, 
        ...