AkAZE是KAZE的加速版

与SIFT,SUFR比较:

1.更加稳定

2.非线性尺度空间

3.AKAZE速度更加快

4.比较新的算法,只有Opencv新的版本才可以用

AKAZE局部匹配介绍

1.AOS构造尺度空间

2.Hessian矩阵特征点

3.方向指定基于一阶微分图像

4.描述子生成

特征点查找和绘制：把surf中的surf改成KAZE或AKAZE即可

#include
#include
#include

using namespace cv;
using namespace cv::features2d;
using namespace std;

int Akaze feature detection(){
Mat src = imread("test.jpg", IMREAD_GRAYSCALE);
if (src.empty()) {
printf("could not load image…\n");
return -1;
}
namedWindow("input image", CV_WINDOW_AUTOSIZE);
imshow("input image", src);

// AKAZE特征点检测  
Ptr<AKAZE> detector = AKAZE::create();//创建一个AKAZE类对象并初始化  
vector<KeyPoint> keypoints;  
detector->detect(src, keypoints, Mat());//找Mat src = imread("test.jpg", IMREAD\_GRAYSCALE);  
if (src.empty()) {  
    printf("could not load image...\\n");  
    return -1;  
}  
namedWindow("input image", CV\_WINDOW\_AUTOSIZE);  
imshow("input image", src);

// AKAZE特征点检测  
Ptr<AKAZE> detector = AKAZE::create();//创建一个AKAZE类对象并初始化  
vector<KeyPoint> keypoints;  
detector->detect(src, keypoints, Mat());//找出关键点

// 绘制关键点  
Mat keypoint\_img;  
drawKeypoints(src, keypoints, keypoint\_img, Scalar::all(-1), DrawMatchesFlags::DEFAULT);  
imshow("KeyPoints Image", keypoint\_img);

waitKey(0);  
return 0;  

}

匹配：

int featurematching{

Mat img1 = imread("/home/leoxae/KeekoRobot/TestPic/qrcodetest/13.png");
Mat img2 = imread("/home/leoxae/KeekoRobot/TestPic/qrcodetest/13.png");

imshow("box image", img1);
imshow("scene image", img2);

// extract akaze features
Ptr detector = AKAZE::create();
vector keypoints_obj;
vector keypoints_scene;
Mat descriptor_obj, descriptor_scene;
detector->detectAndCompute(img1, Mat(), keypoints_obj, descriptor_obj);
detector->detectAndCompute(img2, Mat(), keypoints_scene, descriptor_scene);

// matching
FlannBasedMatcher matcher(new flann::LshIndexParams(20, 10, 2));
//FlannBasedMatcher matcher;
vector matches;
matcher.match(descriptor_obj, descriptor_scene, matches);

// draw matches(key points)
Mat akazeMatchesImg;
/*
drawMatches(img1, keypoints_obj, img2, keypoints_scene, matches, akazeMatchesImg);
imshow("akaze match result", akazeMatchesImg);*/

vector goodMatches;
double minDist = 100000, maxDist = 0;
for (int i = 0; i < descriptor_obj.rows; i++) { double dist = matches[i].distance; if (dist < minDist) { minDist = dist; } if (dist > maxDist) {
maxDist = dist;
}
}
printf("min distance : %f", minDist);

for (int i = 0; i < descriptor_obj.rows; i++) {
double dist = matches[i].distance;
if (dist < max( 1.5*minDist, 0.02)) {
goodMatches.push_back(matches[i]);
}
}

drawMatches(img1, keypoints_obj, img2, keypoints_scene, goodMatches, akazeMatchesImg, Scalar::all(-1),
Scalar::all(-1), vector(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
imshow("good match result", akazeMatchesImg);
waitKey(0);
}