【笔记】Opencv 中 Sift算子：特征提取与匹配

#include "highgui/highgui.hpp"
#include "opencv2/nonfree/nonfree.hpp"
#include "opencv2/legacy/legacy.hpp"
 
using namespace cv;
 
int main(int argc,char *argv[])
{
	Mat image01=imread(argv[1]);
	Mat image02=imread(argv[2]);
	Mat image1,image2;
	GaussianBlur(image01,image1,Size(3,3),0.5);
	GaussianBlur(image02,image2,Size(3,3),0.5);
 
	//提取特征点
	SiftFeatureDetector siftDetector(30);  //限定提起前15个特征点
	vector<KeyPoint> keyPoint1,keyPoint2;
	siftDetector.detect(image1,keyPoint1);
	siftDetector.detect(image2,keyPoint2);
 
	//绘制特征点
	drawKeypoints(image1,keyPoint1,image1,Scalar::all(-1),DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
	drawKeypoints(image2,keyPoint2,image2,Scalar::all(-1),DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
	namedWindow("KeyPoints of image1",0);
	namedWindow("KeyPoints of image2",0);
 
	imshow("KeyPoints of image1",image1);
	imshow("KeyPoints of image2",image2);
 
	//特征点描述，为下边的特征点匹配做准备
	SiftDescriptorExtractor siftDescriptor;
	Mat imageDesc1,imageDesc2;
	siftDescriptor.compute(image1,keyPoint1,imageDesc1);
	siftDescriptor.compute(image2,keyPoint2,imageDesc2);
 
	//特征点匹配并显示匹配结果
	BruteForceMatcher<L2<float>> matcher;
	vector<DMatch> matchePoints;
	matcher.match(imageDesc1,imageDesc2,matchePoints,Mat());
	Mat imageOutput;
	drawMatches(image01,keyPoint1,image02,keyPoint2,matchePoints,imageOutput);
	namedWindow("Mathch Points",0);
	imshow("Mathch Points",imageOutput);
	waitKey();
	return 0;
}