SIFT匹配算法分析(Practical OpenCV)

1、源程序

#include<opencv2/opencv.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/nonfree/features2d.hpp>
#include<opencv2/features2d/features2d.hpp>

using namespace std;
using namespace cv;


int main()
{
	Mat train=imread("OpticalFlow0.jpg"),train_g;
	cvtColor(train,train_g,CV_RGB2GRAY);

	vector<KeyPoint> train_kp;
	Mat train_desc;

	SiftFeatureDetector featureDetector;
	featureDetector.detect(train_g,train_kp);
	SiftDescriptorExtractor featureExtractor;
	featureExtractor.compute(train_g,train_kp,train_desc);


	BFMatcher matcher(NORM_L2);
	vector<Mat> train_desc_collection(1,train_desc);//??????????
	matcher.add(train_desc_collection);
	matcher.train();

	Mat test=imread("OpticalFlow1.jpg");//初始化
	Mat test_g;


	cvtColor(test,test_g,CV_RGB2GRAY);


	vector<KeyPoint> test_kp;
	Mat  test_desc;
	featureDetector.detect(test_g,test_kp);
	featureExtractor.compute(test_g,test_kp,test_desc);
	vector<vector<DMatch> > matches;

	matcher.knnMatch(test_desc,matches,2);


	vector<DMatch> good_matches;
	for(int i=0;i<matches.size();i++)
	{
		if(matches[i][0].distance<0.6*matches[i][1].distance)
			good_matches.push_back(matches[i][0]);

	}

	Mat img_show;
	drawMatches(test,test_kp,train,train_kp,good_matches,img_show);
	imshow("Matches",img_show);

	waitKey();

	return 1;



}

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