Opencv - 多项式函数拟合
Opencv - polynomial function fitting
在opencv(或其他c++ lib)中,是否有类似matlab fit
的函数可以进行3d多项式曲面拟合(即f(x,y)= p00 + p10*x + p01*y + p20*x^2 + p11*x*y + p02*y^2
)。谢谢
我认为 opencv 中没有库,但您可以这样做:
int main( int argc, char** argv )
{
Mat z = imread("1449862093156643.jpg",CV_LOAD_IMAGE_GRAYSCALE);
Mat M = Mat_<double>(z.rows*z.cols,6);
Mat I=Mat_<double>(z.rows*z.cols,1);
for (int i=0;i<z.rows;i++)
for (int j = 0; j < z.cols; j++)
{
double x=(j - z.cols / 2) / double(z.cols),y= (i - z.rows / 2) / double(z.rows);
M.at<double>(i*z.cols+j, 0) = x*x;
M.at<double>(i*z.cols+j, 1) = y*y;
M.at<double>(i*z.cols+j, 2) = x*y;
M.at<double>(i*z.cols+j, 3) = x;
M.at<double>(i*z.cols+j, 4) = y;
M.at<double>(i*z.cols+j, 5) = 1;
I.at<double>(i*z.cols+j, 0) = z.at<uchar>(i,j);
}
SVD s(M);
Mat q;
s.backSubst(I,q);
cout<<q;
imshow("Orignal",z);
cout<<q.at<double>(2,0);
Mat background(z.rows,z.cols,CV_8UC1);
for (int i=0;i<z.rows;i++)
for (int j = 0; j < z.cols; j++)
{
double x=(j - z.cols / 2) / double(z.cols),y= (i - z.rows / 2) / double(z.rows);
double quad=q.at<double>(0,0)*x*x+q.at<double>(1,0)*y*y+q.at<double>(2,0)*x*y;
quad+=q.at<double>(3,0)*x+q.at<double>(4,0)*y+q.at<double>(5,0);
background.at<uchar>(i,j) = saturate_cast<uchar>(quad);
}
imshow("Simulated background",background);
waitKey();
return 0;
}
openCV (contrib.hpp) 中有一个名为 cv::polyfit()
的未记录函数。它以一个 Mat
的 x 坐标和另一个 Mat
的 y 坐标作为输入。为此使用 Mats 不是很容易,但您可以构建一个包装器来发送 vector
个 cv::Point
点。
vector <float> fitPoly(const vector <Point> &src, int order){
Mat src_x = Mat(src.size(), 1, CV_32F);
Mat src_y = Mat(src.size(), 1, CV_32F);
for (int i = 0; i < src.size(); i++){
src_x.at<float>(i, 0) = (float)src[i].x;
src_y.at<float>(i, 0) = (float)src[i].y;
}
return cv::polyfit(src_x, src_y, order);
}
在opencv(或其他c++ lib)中,是否有类似matlab fit
的函数可以进行3d多项式曲面拟合(即f(x,y)= p00 + p10*x + p01*y + p20*x^2 + p11*x*y + p02*y^2
)。谢谢
我认为 opencv 中没有库,但您可以这样做:
int main( int argc, char** argv )
{
Mat z = imread("1449862093156643.jpg",CV_LOAD_IMAGE_GRAYSCALE);
Mat M = Mat_<double>(z.rows*z.cols,6);
Mat I=Mat_<double>(z.rows*z.cols,1);
for (int i=0;i<z.rows;i++)
for (int j = 0; j < z.cols; j++)
{
double x=(j - z.cols / 2) / double(z.cols),y= (i - z.rows / 2) / double(z.rows);
M.at<double>(i*z.cols+j, 0) = x*x;
M.at<double>(i*z.cols+j, 1) = y*y;
M.at<double>(i*z.cols+j, 2) = x*y;
M.at<double>(i*z.cols+j, 3) = x;
M.at<double>(i*z.cols+j, 4) = y;
M.at<double>(i*z.cols+j, 5) = 1;
I.at<double>(i*z.cols+j, 0) = z.at<uchar>(i,j);
}
SVD s(M);
Mat q;
s.backSubst(I,q);
cout<<q;
imshow("Orignal",z);
cout<<q.at<double>(2,0);
Mat background(z.rows,z.cols,CV_8UC1);
for (int i=0;i<z.rows;i++)
for (int j = 0; j < z.cols; j++)
{
double x=(j - z.cols / 2) / double(z.cols),y= (i - z.rows / 2) / double(z.rows);
double quad=q.at<double>(0,0)*x*x+q.at<double>(1,0)*y*y+q.at<double>(2,0)*x*y;
quad+=q.at<double>(3,0)*x+q.at<double>(4,0)*y+q.at<double>(5,0);
background.at<uchar>(i,j) = saturate_cast<uchar>(quad);
}
imshow("Simulated background",background);
waitKey();
return 0;
}
openCV (contrib.hpp) 中有一个名为 cv::polyfit()
的未记录函数。它以一个 Mat
的 x 坐标和另一个 Mat
的 y 坐标作为输入。为此使用 Mats 不是很容易,但您可以构建一个包装器来发送 vector
个 cv::Point
点。
vector <float> fitPoly(const vector <Point> &src, int order){
Mat src_x = Mat(src.size(), 1, CV_32F);
Mat src_y = Mat(src.size(), 1, CV_32F);
for (int i = 0; i < src.size(); i++){
src_x.at<float>(i, 0) = (float)src[i].x;
src_y.at<float>(i, 0) = (float)src[i].y;
}
return cv::polyfit(src_x, src_y, order);
}