opencv_C++ AKAZE 特征提取与匹配

一、程序示例及注释

#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>

using namespace cv;
using namespace std;

int main()
{
	Mat objImage = imread("curry1.jpg", 0);
	Mat sceneImage = imread("curry_dlt.jpg", 0);

	// kaze detection
	Ptr<AKAZE> detector = AKAZE::create();
	vector<KeyPoint> obj_keypoints, scene_keypoints;
	Mat obj_descriptor, scene_descriptor;

	double t1 = getTickCount();
	// 得到keypoints 和 描述子
	detector->detectAndCompute(objImage, Mat(), obj_keypoints, obj_descriptor);
	detector->detectAndCompute(sceneImage, Mat(), scene_keypoints, scene_descriptor);
	double t2 = getTickCount();

	// 使用的时间
	double d_kazeTime = 1000 * (t2 - t1) / getTickFrequency();
	printf("Use time is: %f\n", d_kazeTime);

	// matching
	BFMatcher matcher(NORM_L2);
	vector<DMatch> matches;
	matcher.match(obj_descriptor, scene_descriptor, matches);
	// draw matches -key points
	Mat akazeMatchesImage;
	drawMatches(objImage, obj_keypoints, sceneImage, scene_keypoints, matches, akazeMatchesImage);
	imshow("akazeMatchesIamge", akazeMatchesImage);

	// good matches
	vector<DMatch> goodMatches;
	double minDist = 10000, maxDist = 0;
	for (size_t i = 0; i < matches.size(); i++)
	{
		double dist = matches[i].distance;
		if (dist < minDist)
			minDist = dist;
		if (dist > maxDist)
			maxDist = dist;
	}
	      
	for (size_t i = 0; i < matches.size(); i++)
	{
		double dist = matches[i].distance;
		if (dist < max(3 * minDist, 0.02))
			goodMatches.push_back(matches[i]);
	}

	Mat goodMathcesImage;
	drawMatches(objImage, obj_keypoints, sceneImage, scene_keypoints, goodMatches, goodMathcesImage,\
		Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
	imshow("goodMathcesImage", goodMathcesImage);

	waitKey(0);
	return 0;
}

二、运行结果