Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
OpenCV 3 Computer Vision Application Programming Cookbook

You're reading from   OpenCV 3 Computer Vision Application Programming Cookbook Recipes to make your applications see

Arrow left icon
Product type Paperback
Published in Feb 2017
Publisher
ISBN-13 9781786469717
Length 474 pages
Edition 3rd Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Robert Laganiere Robert Laganiere
Author Profile Icon Robert Laganiere
Robert Laganiere
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. Playing with Images FREE CHAPTER 2. Manipulating Pixels 3. Processing the Colors of an Image 4. Counting the Pixels with Histograms 5. Transforming Images with Morphological Operations 6. Filtering the Images 7. Extracting Lines, Contours, and Components 8. Detecting Interest Points 9. Describing and Matching Interest Points 10. Estimating Projective Relations in Images 11. Reconstructing 3D Scenes 12. Processing Video Sequences 13. Tracking Visual Motion 14. Learning from Examples

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 estimate the exact 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...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime