AKAZE局部匹配

AKAZE局部匹配介绍
AOS 构造尺度空间
Hessian矩阵特征点检测
方向指定基于一阶微分图像
描述子生成

与SIFT、SUFR比较
更加稳定
非线性尺度空间
AKAZE速度更加快
比较新的算法，只有OpenCV新版本才可以用

#include
#include

using namespace cv;
using namespace std;

int main(int argc, char** argv) {
Mat src = imread("D:/vcprojects/images/test.png", IMREAD_GRAYSCALE);
if (src.empty()) {
printf("could not load image…\n");
return -;
}
imshow("input image", src);

// kaze detection  
Ptr<AKAZE> detector = AKAZE::create();  
vector<KeyPoint> keypoints;  
double t1 = getTickCount();  
detector->detect(src, keypoints, Mat());  
double t2 = getTickCount();  
double tkaze =  \* (t2 - t1) / getTickFrequency();  
printf("KAZE Time consume(ms) : %f", tkaze);

Mat keypointImg;  
drawKeypoints(src, keypoints, keypointImg, Scalar::all(-), DrawMatchesFlags::DEFAULT);  
imshow("kaze key points", keypointImg);

waitKey();  
return ;  

}

#include
#include
#include

using namespace cv;
using namespace std;

int main(int argc, char** argv) {
Mat img1 = imread("D:/vcprojects/images/box.png", IMREAD_GRAYSCALE);
Mat img2 = imread("D:/vcprojects/images/box_in_scene.png", IMREAD_GRAYSCALE);
if (img1.empty() || img2.empty()) {
printf("could not load images…\n");
return -;
}
imshow("box image", img1);
imshow("scene image", img2);

// extract akaze features  
Ptr<AKAZE> detector = AKAZE::create();  
vector<KeyPoint> keypoints\_obj;  
vector<KeyPoint> keypoints\_scene;  
Mat descriptor\_obj, descriptor\_scene;  
double t1 = getTickCount();  
detector->detectAndCompute(img1, Mat(), keypoints\_obj, descriptor\_obj);  
detector->detectAndCompute(img2, Mat(), keypoints\_scene, descriptor\_scene);  
double t2 = getTickCount();  
double tkaze =  \* (t2 - t1) / getTickFrequency();  
printf("AKAZE Time consume(ms) : %f\\n", tkaze);

// matching  
FlannBasedMatcher matcher(new flann::LshIndexParams(, , ));  
//FlannBasedMatcher matcher;  
vector<DMatch> 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<DMatch> 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<char>(), DrawMatchesFlags::NOT\_DRAW\_SINGLE\_POINTS);  
imshow("good match result", akazeMatchesImg);  
\*/

waitKey();  
return ;  

}