图像匹配.txt

#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/nonfree/nonfree.hpp>  
#include <opencv2/legacy/legacy.hpp>  
#include <iostream>  

using namespace cv;
using namespace std;

//直接调用此函数
//srcImage1为左，srcImage2为右，paraHessian可直接选择1000-5000的数，keyPoints_min_xiaotu为左图中对应的匹配，keyPoints_min_datu为右图中对应的特征点


void cacSIFTFeatureAndCompare1(cv::Mat srcImage1, cv::Mat srcImage2, float paraHessian, vector<Point2f> &keyPoints_min_xiaotu, vector<Point2f> &keyPoints_min_datu)
{
	CV_Assert(srcImage1.data != NULL && srcImage2.data != NULL);
	Mat grayMat1, grayMat2;
	cvtColor(srcImage1, grayMat1, CV_RGB2GRAY);
	cvtColor(srcImage2, grayMat2, CV_RGB2GRAY);
	SurfFeatureDetector surfDetector(paraHessian);
	SurfDescriptorExtractor surfExtractor;
	vector<KeyPoint> keyPoints1, keyPoints2;
	Mat descriptorMat1, descriptorMat2;
	surfDetector.detect(grayMat1, keyPoints1);
	surfDetector.detect(grayMat2, keyPoints2);
	surfExtractor.compute(grayMat1, keyPoints1, descriptorMat1);
	surfExtractor.compute(grayMat2, keyPoints2, descriptorMat2);
	if (keyPoints1.size() > 0 && keyPoints2.size() > 0)
	{
		cv::FlannBasedMatcher matcher;
		vector< cv::DMatch > matches;
		std::vector<cv::DMatch> viewMatches;
		matcher.match(descriptorMat1, descriptorMat2, matches);
		//最优匹配判断  
		double minDist = 100;
		for (int i = 0; i < matches.size(); i++)
		{
			if (matches[i].distance < minDist)
				minDist = matches[i].distance;
		}
		for (int i = 0; i < matches.size(); i++)
		{
			if (matches[i].distance <= 2 * minDist)
			{
				viewMatches.push_back(matches[i]);
				keyPoints_min_xiaotu.push_back(keyPoints1[matches[i].queryIdx].pt);
				keyPoints_min_datu.push_back(keyPoints2[matches[i].trainIdx].pt);
			}
		}

		Mat matchMat;
		drawMatches(srcImage1, keyPoints1, srcImage2, keyPoints2, viewMatches, matchMat);
		imshow("matchMat", matchMat);
		waitKey();
	}

	
}