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Feature Detection

Table of Contents

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Original author Ana Huamán
Compatibility OpenCV >= 3.0

Goal

In this tutorial you will learn how to:

Warning
You need the OpenCV contrib modules to be able to use the SURF features (alternatives are ORB, KAZE, ... features).

Theory

Code

This tutorial code's is shown lines below. You can also download it from here

#include <iostream>
#include "opencv2/core.hpp"
#ifdef HAVE_OPENCV_XFEATURES2D
using namespace cv;
using namespace cv::xfeatures2d;
using std::cout;
using std::endl;
int main( int argc, char* argv[] )
{
CommandLineParser parser( argc, argv, "{@input | box.png | input image}" );
Mat src = imread( samples::findFile( parser.get<String>( "@input" ) ), IMREAD_GRAYSCALE );
if ( src.empty() )
{
cout << "Could not open or find the image!\n" << endl;
cout << "Usage: " << argv[0] << " <Input image>" << endl;
return -1;
}
//-- Step 1: Detect the keypoints using SURF Detector
int minHessian = 400;
Ptr<SURF> detector = SURF::create( minHessian );
std::vector<KeyPoint> keypoints;
detector->detect( src, keypoints );
//-- Draw keypoints
Mat img_keypoints;
drawKeypoints( src, keypoints, img_keypoints );
//-- Show detected (drawn) keypoints
imshow("SURF Keypoints", img_keypoints );
waitKey();
return 0;
}
#else
int main()
{
std::cout << "This tutorial code needs the xfeatures2d contrib module to be run." << std::endl;
return 0;
}
#endif
Designed for command line parsing.
Definition utility.hpp:890
n-dimensional dense array class
Definition mat.hpp:829
bool empty() const
Returns true if the array has no elements.
std::string String
Definition cvstd.hpp:151
std::shared_ptr< _Tp > Ptr
Definition cvstd_wrapper.hpp:23
int main(int argc, char *argv[])
Definition highgui_qt.cpp:3
Definition xfeatures2d.hpp:67
Definition core.hpp:107

Explanation

Result

  1. Here is the result of the feature detection applied to the box.png image:
  1. And here is the result for the box_in_scene.png image: