Projects\image_match3图像特征匹配调试记录

D:\文件及下载相关\文档\Visual Studio \Projects\image_match3\image_match

#include "opencv2/core/core.hpp"

#include "highgui.h"

#include "opencv2/imgproc/imgproc.hpp"

#include "opencv2/features2d/features2d.hpp"

#include "opencv2/nonfree/nonfree.hpp"

#include "opencv2/legacy/legacy.hpp"

using namespace cv;

using namespace std;

int main(int argc, char** argv)

{

   //待匹配的两幅图像，其中img1包括img2，也就是要从img1中识别出img2

   //Mat img1 = imread("book_in_scene.png");

   //Mat img2 = imread("book2.png");

   Mat img1 = imread("003.png");

   Mat img2 = imread("004.png");

   Mat image01;

   Mat image02;

   cvtColor(img1,image01,CV_RGB2GRAY);

   cvtColor(img2,image02,CV_RGB2GRAY);

   SIFT sift1, sift2;

   vector<KeyPoint> key_points1, key_points2;

   Mat descriptors1, descriptors2, mascara;

   sift1(img1,mascara,key_points1,descriptors1);

   sift2(img2,mascara,key_points2,descriptors2);

   //实例化暴力匹配器——BruteForceMatcher

   BruteForceMatcher<L2<float>> matcher;

   //定义匹配器算子

   vector<DMatch>matches;

   //实现描述符之间的匹配，得到算子matches

   matcher.match(descriptors1,descriptors2,matches);

   //提取出前3个最佳匹配结果

   nth_element(matches.begin(),     //匹配器算子的初始位置

       matches.begin()+,     // 排序的数量

       matches.end());       // 结束位置

   //剔除掉其余的匹配结果

   matches.erase(matches.begin()+, matches.end());

   namedWindow("SIFT_matches");

   Mat img_matches;

   //在输出图像中绘制匹配结果

   drawMatches(img1,key_points1,         //第一幅图像和它的特征点

       img2,key_points2,      //第二幅图像和它的特征点

       matches,       //匹配器算子

       img_matches,      //匹配输出图像

       Scalar(,,));     //用白色直线连接两幅图像中的特征点

   imshow("SIFT_matches",img_matches);

    vector<Point2f> imagePoints1,imagePoints2;

    for(int i=;i<;i++)

    {

        imagePoints1.push_back(key_points1[matches[i].queryIdx].pt);

        imagePoints2.push_back(key_points2[matches[i].trainIdx].pt);

    }

   Mat homo=findHomography(imagePoints1,imagePoints2,CV_RANSAC);

   ////也可以使用getPerspectiveTransform方法获得透视变换矩阵，不过要求只能有4个点，效果稍差  

   //Mat homo=getPerspectiveTransform(imagePoints1,imagePoints2);     

   cout<<"变换矩阵为：\n"<<homo<<endl<<endl;//输出映射矩阵  

   //图像配准  

   Mat imageTransform1,imageTransform2;

   warpPerspective(image01,imageTransform1,homo,Size(image02.cols,image02.rows));

   imshow("经过透视矩阵变换后",imageTransform1);

   waitKey();

   return ;

}

 Mat img1 = imread("003.png");

 Mat img2 = imread("004.png");

测试两个方向拍摄的熊娃娃：

对海面舰船目标的MUSIC高精度定位方法研究(图文) - 期刊论文网 http://www.pinjiao.com/lunwenqikan/kejixiaolunwen/lunwen21906.html