OpenCV: SURF Feature matching

1. Load two images
2. do SURF feature extraction
3. Using Flann matching to match the keypoints
4. Identify good matches
5. find the object in the scene image

	#include <iostream>
	#include <stdio.h>
	#include <stdlib.h>
	#include <vector>
	#include "opencv2\opencv.hpp"
	#include <opencv2\nonfree\features2d.hpp>
	using namespace std;
	using namespace cv;
	int main()
	{
	Mat img_1, img_2;
	//image = imread("lena.jpg",1);
	img_1= imread("Matrix1_small.jpg", CV_LOAD_IMAGE_GRAYSCALE );
	img_2= imread("RoboticsMatrix.jpg", CV_LOAD_IMAGE_GRAYSCALE );
	if(img_1.empty()||img_2.empty())
	{
	cout << "Could not open or find the image" << std::endl ;
	return -1;
	}
	/// Resize
	resize(img_1,img_1,Size(0,0),0.15,0.15,INTER_LINEAR);
	resize(img_2,img_2,Size(0,0),0.2,0.2,INTER_LINEAR);
	imshow("Image 1", img_1);
	imshow("Image 2", img_2);
	// Step -1, Detect keypoints using SURF detector
	int minHessian = 400;
	SurfFeatureDetector detector(minHessian);
	vector<KeyPoint> keypoints_1, keypoints_2;
	detector.detect(img_1, keypoints_1);
	detector.detect(img_2, keypoints_2);
	Mat img_keypoints_1;
	drawKeypoints( img_1, keypoints_1, img_keypoints_1, Scalar::all(-1), DrawMatchesFlags::DEFAULT );
	imshow("Image1 KeyPoints", img_keypoints_1);
	//imwrite("Lena Keypoints.jpg",img_keypoints_1);
	// Step -2, Calculate descriptors (feature vector)
	SurfDescriptorExtractor extractor;
	Mat descriptor_1, descriptor_2;
	extractor.compute(img_1,keypoints_1,descriptor_1);
	extractor.compute(img_2,keypoints_2,descriptor_2);
	//step - 3, Matching descriptor vectors with a brute force mathcher
	double t = (double)getTickCount();
	BFMatcher matcher(NORM_L2);
	vector<DMatch> matches;
	matcher.match(descriptor_1, descriptor_2,matches);
	t = ((double)getTickCount() - t)/getTickFrequency();
	cout << " Brute Force Matching Time (senconds): " << t<<endl;
	// maches with Flann Based Matching.
	t = (double)getTickCount();
	FlannBasedMatcher matcher2;
	vector<DMatch> matches2;
	matcher2.match(descriptor_1,descriptor_2,matches2);
	t = ((double)getTickCount() - t)/getTickFrequency();
	cout << " Flann Based Matching Time (senconds): " << t<<endl;
	//--Draw Matches
	Mat img_matches;
	drawMatches(img_1,keypoints_1,img_2,keypoints_2,matches,img_matches);
	//-- Show Detected Matches
	imshow("Matches Brute",img_matches);
	//--Draw Matches
	Mat img_matches2;
	drawMatches(img_1,keypoints_1,img_2,keypoints_2,matches2,img_matches2);
	//-- Show Detected Matches
	imshow("Matches Flann",img_matches2);
	// quick calcualation of max and min distances between keypoints
	double max_dist=0; double min_dist = 100;
	for (int i =0; i < descriptor_1.rows;i++)
	{
	double dist = matches2[i].distance;
	if(max_dist<dist) max_dist = dist;
	if(min_dist>dist) min_dist = dist;
	}
	vector< DMatch> good_matches;
	for (int i=0;i<descriptor_1.rows;i++)
	{
	if( matches2[i].distance<3*min_dist)
	good_matches.push_back(matches2[i]);
	}
	// Draw Good Matches
	Mat img_goodmatches;
	drawMatches(img_1,keypoints_1,img_2,keypoints_2,good_matches,img_goodmatches,Scalar::all(-1),Scalar::all(-1),vector<char>(),DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
	imshow( "Good Matches", img_goodmatches );
	for( int i = 0; i < good_matches.size(); i++ )
	{
	printf( "-- Good Match [%d] Keypoint 1: %d -- Keypoint 2: %d \n", i, good_matches[i].queryIdx, good_matches[i].trainIdx );
	}
	// Localize the object
	vector<Point2f> obj;
	vector<Point2f> scene;
	for( int i = 0; i < good_matches.size(); i++ )
	{
	obj.push_back(keypoints_1[good_matches[i].queryIdx].pt);
	scene.push_back(keypoints_2[good_matches[i].trainIdx].pt);
	}
	Mat H = findHomography( obj,scene,CV_RANSAC);
	vector<Point2f> obj_corners(4);
	obj_corners[0] = cvPoint(0,0);
	obj_corners[1] = cvPoint(img_1.cols,0);
	obj_corners[2] = cvPoint(img_1.cols,img_1.rows);
	obj_corners[3] = cvPoint(0,img_1.rows);
	std::vector<Point2f> scene_corners(4);
	Mat img_object = img_1.clone();
	perspectiveTransform( obj_corners, scene_corners, H);
	img_matches = img_goodmatches;
	//-- Draw lines between the corners (the mapped object in the scene - image_2 )
	line( img_matches, scene_corners[0] + Point2f( img_object.cols, 0), scene_corners[1] + Point2f( img_object.cols, 0), Scalar(0, 255, 0), 4 );
	line( img_matches, scene_corners[1] + Point2f( img_object.cols, 0), scene_corners[2] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );
	line( img_matches, scene_corners[2] + Point2f( img_object.cols, 0), scene_corners[3] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );
	line( img_matches, scene_corners[3] + Point2f( img_object.cols, 0), scene_corners[0] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );
	//-- Show detected matches
	imshow( "Good Matches & Object detection", img_matches );
	// imwrite("Lena SURF Matches.jpg",img_matches);
	waitKey(0);
	return 0;
	}

view raw gistfile1.cpp hosted with ❤ by GitHub