根据Opencv中检测到的功能对齐图像
嗨，我有一个基础图像和其他图像，我想旋转与基本图像相同的角度。
这是我的基本形象。
这是我想要旋转的示例图像。
这里是我的完整代码。
#include <stdio.h>
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/nonfree/nonfree.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#define PI 3.14159265
using namespace cv;
using namespace std;
void rotate(cv::Mat& src, double angle, cv::Mat& dst)
{
int len = std::max(src.cols, src.rows);
cv::Point2f pt(len/2., len/2.);
cv::Mat r = cv::getRotationMatrix2D(pt, angle, 1.0);
cv::warpAffine(src, dst, r, cv::Size(len, len));
}
float angleBetween(const Point &v1, const Point &v2)
{
float len1 = sqrt(v1.x * v1.x + v1.y * v1.y);
float len2 = sqrt(v2.x * v2.x + v2.y * v2.y);
float dot = v1.x * v2.x + v1.y * v2.y;
float a = dot / (len1 * len2);
if (a >= 1.0)
return 0.0;
else if (a <= -1.0)
return PI;
else{
int degree;
degree = acos(a)*180/PI;
return degree;
};
}
int main()
{
Mat char1 = imread( "/Users/Rodrane/Documents/XCODE/OpenCV/mkedenemeleri/anarev/rotated.jpg",CV_LOAD_IMAGE_GRAYSCALE );
Mat image = imread("/Users/Rodrane/Documents/XCODE/OpenCV/mkedenemeleri/anarev/gain2000_crop.jpg", CV_LOAD_IMAGE_GRAYSCALE );
if( !char1.data )
{
std::cout<< "Error reading object " << std::endl;
return -1;
}
GaussianBlur( char1, char1, Size(3, 3), 2, 2 );
GaussianBlur( image, image, Size(3, 3), 2, 2 );
adaptiveThreshold(char1,char1,255,CV_ADAPTIVE_THRESH_MEAN_C,CV_THRESH_BINARY,9,14);
adaptiveThreshold(image,image,255,CV_ADAPTIVE_THRESH_MEAN_C,CV_THRESH_BINARY,9,14);
//Detect the keypoints using SURF Detector
int minHessian = 200;
SurfFeatureDetector detector( minHessian );
std::vector<KeyPoint> kp_object;
detector.detect( char1, kp_object );
//Calculate descriptors (feature vectors)
SurfDescriptorExtractor extractor;
Mat des_object;
extractor.compute( char1, kp_object, des_object );
FlannBasedMatcher matcher;
namedWindow("Good Matches");
std::vector<Point2f> obj_corners(4);
//Get the corners from the object
obj_corners[0] = cvPoint(0,0);
obj_corners[1] = cvPoint( char1.cols, 0 );
obj_corners[2] = cvPoint( char1.cols, char1.rows );
obj_corners[3] = cvPoint( 0, char1.rows );
Mat frame;
Mat des_image, img_matches;
std::vector<KeyPoint> kp_image;
std::vector<vector<DMatch > > matches;
std::vector<DMatch > good_matches;
std::vector<Point2f> obj;
std::vector<Point2f> scene;
std::vector<Point2f> scene_corners(4);
Mat H;
detector.detect( image, kp_image );
extractor.compute( image, kp_image, des_image );
matcher.knnMatch(des_object, des_image, matches, 2);
for(int i = 0; i < min(des_image.rows-1,(int) matches.size()); i++) //THIS LOOP IS SENSITIVE TO SEGFAULTS
{
if((matches[i][0].distance < 0.6*(matches[i][1].distance)) && ((int) matches[i].size()<=2 && (int) matches[i].size()>0))
{
good_matches.push_back(matches[i][0]);
}
}
//Draw only "good" matches
drawMatches( char1, kp_object, image, kp_image, good_matches, img_matches, Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
if (good_matches.size() >= 4)
{
for( int i = 0; i < good_matches.size(); i++ )
{
//Get the keypoints from the good matches
obj.push_back( kp_object[ good_matches[i].queryIdx ].pt );
scene.push_back( kp_image[ good_matches[i].trainIdx ].pt );
cout<<angleBetween(obj[i],scene[i])<<endl; //angles between images
}
H = findHomography( obj, scene, CV_RANSAC );
perspectiveTransform( obj_corners, scene_corners, H);
// cout<<angleBetween(obj[0], scene[0])<<endl;
//Draw lines between the corners (the mapped object in the scene image )
}
//Show detected matches
// resize(img_matches, img_matches, Size(img_matches.cols/2, img_matches.rows/2));
imshow( "Good Matches", img_matches );
waitKey();
return 0;
}
我的代码实际上是什么;
因为点之间的所有度数都不同，我怎样根据特性来旋转我的图像？
例如，假设检测到字符M的特征，并且在某些情况下角度为30，则旋转30度的图像会使我水平对齐但垂直错误。
问题是即使第一个功能在同一行，这并不意味着示例图像正确旋转（例如，它可能需要旋转180度）
我没有使用角度重拍你的功能：
void rotate(cv::Mat& originalImage,cv::Mat& rotatedImage,cv::InputArray rotated,
cv::Mat& dst) {
std::vector<cv::Point2f> original(4);
original[0] = cv::Point( 0, 0);
original[1] = cv::Point( originalImage.cols, 0 );
original[2] = cv::Point( originalImage.cols, originalImage.rows );
original[3] = cv::Point( 0, originalImage.rows );
dst = cv::Mat::zeros(originalImage.rows, originalImage.cols, CV_8UC3);
cv::Mat transform = cv::getPerspectiveTransform(rotated, original);
cv::warpPerspective(rotatedImage, dst, transform, dst.size() );
}
请注意，输入'旋转'是你的情况'scene_corners'和'dst'是结果图像。
希望有所帮助！
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