OpenCV  3.2.0
Open Source Computer Vision
Feature Detection

.2.0+dfsg_doc_tutorials_features2d_feature_detection_feature_detection

Goal

In this tutorial you will learn how to:

  • Use the cv::FeatureDetector interface in order to find interest points. Specifically:
    • Use the cv::xfeatures2d::SURF and its function cv::xfeatures2d::SURF::detect to perform the detection process
    • Use the function cv::drawKeypoints to draw the detected keypoints

Theory

Code

This tutorial code's is shown lines below.

#include <stdio.h>
#include <iostream>
#include "opencv2/core.hpp"
#include "opencv2/xfeatures2d.hpp"
using namespace cv;
using namespace cv::xfeatures2d;
void readme();
/* @function main */
int main( int argc, char** argv )
{
if( argc != 3 )
{ readme(); return -1; }
Mat img_1 = imread( argv[1], IMREAD_GRAYSCALE );
Mat img_2 = imread( argv[2], IMREAD_GRAYSCALE );
if( !img_1.data || !img_2.data )
{ std::cout<< " --(!) Error reading images " << std::endl; return -1; }
//-- Step 1: Detect the keypoints using SURF Detector
int minHessian = 400;
Ptr<SURF> detector = SURF::create( minHessian );
std::vector<KeyPoint> keypoints_1, keypoints_2;
detector->detect( img_1, keypoints_1 );
detector->detect( img_2, keypoints_2 );
//-- Draw keypoints
Mat img_keypoints_1; Mat img_keypoints_2;
drawKeypoints( img_1, keypoints_1, img_keypoints_1, Scalar::all(-1), DrawMatchesFlags::DEFAULT );
drawKeypoints( img_2, keypoints_2, img_keypoints_2, Scalar::all(-1), DrawMatchesFlags::DEFAULT );
//-- Show detected (drawn) keypoints
imshow("Keypoints 1", img_keypoints_1 );
imshow("Keypoints 2", img_keypoints_2 );
waitKey(0);
return 0;
}
/* @function readme */
void readme()
{ std::cout << " Usage: ./SURF_detector <img1> <img2>" << std::endl; }

Explanation

Result

  1. Here is the result of the feature detection applied to the first image:

  2. And here is the result for the second image:

cv::Scalar_< double >::all
static Scalar_< double > all(double v0)
returns a scalar with all elements set to v0
cv::waitKey
int waitKey(int delay=0)
Waits for a pressed key.
highgui.hpp
cv::IMREAD_GRAYSCALE
@ IMREAD_GRAYSCALE
If set, always convert image to the single channel grayscale image.
Definition: imgcodecs.hpp:66
cv::imread
Mat imread(const String &filename, int flags=IMREAD_COLOR)
Loads an image from a file.
cv::DrawMatchesFlags::DEFAULT
@ DEFAULT
Definition: features2d.hpp:1117
cv::Ptr
Template class for smart pointers with shared ownership.
Definition: cvstd.hpp:281
cv::imshow
void imshow(const String &winname, InputArray mat)
Displays an image in the specified window.
features2d.hpp
cv::Mat
n-dimensional dense array class
Definition: mat.hpp:741
core.hpp
cv
Definition: affine.hpp:52
cv::drawKeypoints
void drawKeypoints(InputArray image, const std::vector< KeyPoint > &keypoints, InputOutputArray outImage, const Scalar &color=Scalar::all(-1), int flags=DrawMatchesFlags::DEFAULT)
Draws keypoints.
cv::Mat::data
uchar * data
pointer to the data
Definition: mat.hpp:1961