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http://blog.csdn.net/dcrmg/article/details/52578732

 

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#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("1.jpg");

Mat image02 = imread("2.jpg");

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;

}

 

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