特徵檢測與匹配(二)——SIFT特徵點匹配

1.SIFT特徵點提取

2.繪製特徵點

3.特徵點描述符(特徵向量)提取

4.使用暴力匹配器進行暴力匹配

5.對匹配結果進行篩選（依據DMatch結構體中的float型別變數distance進行篩選）

6.繪製匹配結果

先上ppt：

程式碼：SIFT特徵點匹配

///SIFT特徵點匹配
#include "opencv2/opencv.hpp"
using namespace cv;
#include "opencv2/nonfree/nonfree.hpp"//SIFT相關
#include "opencv2/legacy/legacy.hpp"//匹配器相關
#include <iostream>
using namespace std;
int main()
{
	//1.SIFT特徵點提取——detect()方法
	Mat srcImg1 = imread("1.jpg", CV_LOAD_IMAGE_COLOR);
	Mat srcImg2 = imread("2.jpg", CV_LOAD_IMAGE_COLOR);
	Mat dstImg1, dstImg2;
	SiftFeatureDetector siftDetector;//SiftFeatureDetector是SIFT類的別名  
	vector<KeyPoint> keyPoints1;
	vector<KeyPoint> keyPoints2;
	siftDetector.detect(srcImg1, keyPoints1);
	siftDetector.detect(srcImg2, keyPoints2);
	drawKeypoints(srcImg1, keyPoints1, dstImg1);
	drawKeypoints(srcImg2, keyPoints2, dstImg2);
	imshow("dstImg1", dstImg1);
	imshow("dstImg2", dstImg2);
	//2.特徵點描述符(特徵向量)提取——compute()方法
	SiftDescriptorExtractor descriptor;//SiftDescriptorExtractor是SIFT類的別名  
	Mat description1;
	Mat description2;
	descriptor.compute(srcImg1, keyPoints1, description1);//注意原圖和特徵點要對應，不要寫錯
	descriptor.compute(srcImg2, keyPoints2, description2);
	imshow("description1", description1);
	imshow("description2", description2);
	//3.使用暴力匹配器進行暴力匹配——BruteForceMatcher類的match()方法
	BruteForceMatcher<L2<float>> matcher;//例項化暴力匹配器
	vector<DMatch> matches; //定義匹配結果變數
	matcher.match(description1, description2, matches);//實現描述符之間的匹配
	//4.對匹配結果進行篩選（依據DMatch結構體中的float型別變數distance進行篩選）
	float minDistance = 100;
	float maxDistance = 0;
	for (int i = 0; i < matches.size(); i++)
	{
		if (matches[i].distance < minDistance)
			minDistance = matches[i].distance;
		if (matches[i].distance > maxDistance)
			maxDistance = matches[i].distance;
	}
	cout << "minDistance: " << minDistance << endl;
	cout << "maxDistance: " << maxDistance << endl;
	vector<DMatch> goodMatches;
	for (int i = 0; i < matches.size(); i++)
	{
		if (matches[i].distance < 2 * minDistance)
		{
			goodMatches.push_back(matches[i]);
		}
	}
	//5.繪製匹配結果——drawMatches()
	Mat dstImg3;
	drawMatches(srcImg1, keyPoints1, srcImg2, keyPoints2, goodMatches, dstImg3);
	imshow("dstImg3", dstImg3);
	waitKey(0);
	return 0;
}
 

執行結果：