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| #include <opencv2/opencv.hpp>
#import "OpenCVTool.h"
using namespace std;
using namespace cv;
const float inlier_threshold = 2.5f; // Distance threshold to identify inliers with homography check
const float nn_match_ratio = 0.8f;
+(BOOL)checkImage:(NSString *)path1 withImage:(NSString *)path2
{
const char * cpath = [path1 cStringUsingEncoding:NSUTF8StringEncoding];
const char * cpath1 = [path2 cStringUsingEncoding:NSUTF8StringEncoding];
Mat img1 = imread(cpath, IMREAD_GRAYSCALE);
Mat img2 = imread(cpath1, IMREAD_GRAYSCALE);
Mat homography;
vector<KeyPoint> kpts1, kpts2;
Mat desc1, desc2;
Ptr<AKAZE> akaze = AKAZE::create();
akaze->detectAndCompute(img1, noArray(), kpts1, desc1);
akaze->detectAndCompute(img2, noArray(), kpts2, desc2);
BFMatcher matcher(NORM_HAMMING);
vector< vector<DMatch> > nn_matches;
matcher.knnMatch(desc1, desc2, nn_matches, 2);
//--------------------
vector<KeyPoint> matched1, matched2;
vector<Point2f> obj, scene;
for(size_t i = 0; i < nn_matches.size(); i++) {
DMatch first = nn_matches[i][0];
float dist1 = nn_matches[i][0].distance;
float dist2 = nn_matches[i][1].distance;
if(dist1 < nn_match_ratio * dist2) {
matched1.push_back(kpts1[first.queryIdx]);
matched2.push_back(kpts2[first.trainIdx]);
//-- Get the keypoints from the good matches
obj.push_back( kpts1[first.queryIdx].pt );
scene.push_back( kpts2[first.trainIdx].pt );
}
}
homography = findHomography( obj, scene, RANSAC );
vector<DMatch> good_matches;
vector<KeyPoint> inliers1, inliers2;
for(size_t i = 0; i < matched1.size(); i++) {
Mat col = Mat::ones(3, 1, CV_64F);
col.at<double>(0) = matched1[i].pt.x;
col.at<double>(1) = matched1[i].pt.y;
col = homography * col;
col /= col.at<double>(2);
double dist = sqrt( pow(col.at<double>(0) - matched2[i].pt.x, 2) +
pow(col.at<double>(1) - matched2[i].pt.y, 2));
if(dist < inlier_threshold) {
int new_i = static_cast<int>(inliers1.size());
inliers1.push_back(matched1[i]);
inliers2.push_back(matched2[i]);
good_matches.push_back(DMatch(new_i, new_i, 0));
}
}
double inlier_ratio = inliers1.size() / (double) matched1.size();
double match = (double) matched1.size()/inliers2.size() ;
cout << "A-KAZE Matching Results" << endl;
cout << "*******************************" << endl;
cout << "# Keypoints 1: \t" << kpts1.size() << endl;
cout << "# Keypoints 2: \t" << kpts2.size() << endl;
cout << "# Matches: \t" << matched1.size() << endl;
cout << "# Inliers: \t" << inliers1.size() << endl;
cout << "# Inliers Ratio: \t" << inlier_ratio << endl;
cout << endl;
if (inlier_ratio >= 0.7&&match>0.15) {
return YES;
}else
{
return NO;
}
}
|
主要参考例子例子1例子2
其中homography 需要自己计算一下
