结构光：光条中心线提取-Steger算法（基于Hessian矩阵）
光条中心线提取-Steger算法（基于Hessian矩阵）
参考以下博客进行了修改，修改了灰度阈值以及最后标注红线的部分。https://blog.csdn.net/dangkie/article/details/78996761#comments
void StegerLine()
{
Mat img0 = imread("D:\\结构光实验数据\\2019-11-20\\1_nl.bmp", 1);
Mat img;
cvtColor(img0, img0, CV_BGR2GRAY);
img = img0.clone();
//高斯滤波
img.convertTo(img, CV_32FC1);
GaussianBlur(img, img, Size(0, 0), 6, 6);
//一阶偏导数
Mat m1, m2;
m1 = (Mat_<float>(1, 2) << 1, -1); //x偏导
m2 = (Mat_<float>(2, 1) << 1, -1); //y偏导
Mat dx, dy;
filter2D(img, dx, CV_32FC1, m1);
filter2D(img, dy, CV_32FC1, m2);
//二阶偏导数
Mat m3, m4, m5;
m3 = (Mat_<float>(1, 3) << 1, -2, 1); //二阶x偏导
m4 = (Mat_<float>(3, 1) << 1, -2, 1); //二阶y偏导
m5 = (Mat_<float>(2, 2) << 1, -1, -1, 1); //二阶xy偏导
Mat dxx, dyy, dxy;
filter2D(img, dxx, CV_32FC1, m3);
filter2D(img, dyy, CV_32FC1, m4);
filter2D(img, dxy, CV_32FC1, m5);
//hessian矩阵
double maxD = -1;
int imgcol = img.cols;
int imgrow = img.rows;
vector<double> Pt;
for (int i = 0; i<imgcol; i++)
{
for (int j = 0; j<imgrow; j++)
{
if (img0.at<uchar>(j, i)>50)
{
Mat hessian(2, 2, CV_32FC1);
hessian.at<float>(0, 0) = dxx.at<float>(j, i);
hessian.at<float>(0, 1) = dxy.at<float>(j, i);
hessian.at<float>(1, 0) = dxy.at<float>(j, i);
hessian.at<float>(1, 1) = dyy.at<float>(j, i);
Mat eValue;
Mat eVectors;
eigen(hessian, eValue, eVectors);
double nx, ny;
double fmaxD = 0;
if (fabs(eValue.at<float>(0, 0)) >= fabs(eValue.at<float>(1, 0))) //求特征值最大时对应的特征向量
{
nx = eVectors.at<float>(0, 0);
ny = eVectors.at<float>(0, 1);
fmaxD = eValue.at<float>(0, 0);
}
else
{
nx = eVectors.at<float>(1, 0);
ny = eVectors.at<float>(1, 1);
fmaxD = eValue.at<float>(1, 0);
}
double t = -(nx*dx.at<float>(j, i) + ny*dy.at<float>(j, i)) / (nx*nx*dxx.at<float>(j, i) + 2 * nx*ny*dxy.at<float>(j, i) + ny*ny*dyy.at<float>(j, i));
if (fabs(t*nx) <= 0.5 && fabs(t*ny) <= 0.5)
{
Pt.push_back(i);
Pt.push_back(j);
}
}
}
}
cvtColor(img0, img0, CV_GRAY2BGR);
for (int k = 0; k<Pt.size() / 2; k++)
{
Point rpt;
rpt.x = Pt[2 * k + 0];
rpt.y = Pt[2 * k + 1];
circle(img0, rpt, 1, Scalar(0, 0, 255));
}
namedWindow("result", CV_WINDOW_NORMAL);
imshow("result", img0);
imwrite("output.bmp", img0);
waitKey(0);
}
修改后的接口
vector<Point> StegerLine(cv::Mat& InputImg)
{
Mat img0 = InputImg;//此为原图，有背景
Mat img;//此为处理图
img0.copyTo(img);//拷贝矩阵
//高斯滤波
img.convertTo(img, CV_32FC1);
GaussianBlur(img, img, Size(0, 0), 6, 6);
//一阶偏导数
Mat m1, m2;
m1 = (Mat_<float>(1, 2) << 1, -1); //x偏导
m2 = (Mat_<float>(2, 1) << 1, -1); //y偏导
Mat dx, dy;
filter2D(img, dx, CV_32FC1, m1);
filter2D(img, dy, CV_32FC1, m2);
//二阶偏导数
Mat m3, m4, m5;
m3 = (Mat_<float>(1, 3) << 1, -2, 1); //二阶x偏导
m4 = (Mat_<float>(3, 1) << 1, -2, 1); //二阶y偏导
m5 = (Mat_<float>(2, 2) << 1, -1, -1, 1); //二阶xy偏导
Mat dxx, dyy, dxy;
filter2D(img, dxx, CV_32FC1, m3);
filter2D(img, dyy, CV_32FC1, m4);
filter2D(img, dxy, CV_32FC1, m5);
//hessian矩阵
double maxD = -1;
int imgcol = img.cols;
int imgrow = img.rows;
vector<double> Pt;
for (int i = 0; i<imgcol; i++)
{
for (int j = 0; j<imgrow; j++)
{
if (img0.at<uchar>(j, i)>50)
{
Mat hessian(2, 2, CV_32FC1);
hessian.at<float>(0, 0) = dxx.at<float>(j, i);
hessian.at<float>(0, 1) = dxy.at<float>(j, i);
hessian.at<float>(1, 0) = dxy.at<float>(j, i);
hessian.at<float>(1, 1) = dyy.at<float>(j, i);
Mat eValue;
Mat eVectors;
eigen(hessian, eValue, eVectors);
double nx, ny;
double fmaxD = 0;
if (fabs(eValue.at<float>(0, 0)) >= fabs(eValue.at<float>(1, 0))) //求特征值最大时对应的特征向量
{
nx = eVectors.at<float>(0, 0);
ny = eVectors.at<float>(0, 1);
fmaxD = eValue.at<float>(0, 0);
}
else
{
nx = eVectors.at<float>(1, 0);
ny = eVectors.at<float>(1, 1);
fmaxD = eValue.at<float>(1, 0);
}
double t = -(nx*dx.at<float>(j, i) + ny*dy.at<float>(j, i)) / (nx*nx*dxx.at<float>(j, i) + 2 * nx*ny*dxy.at<float>(j, i) + ny*ny*dyy.at<float>(j, i));
if (fabs(t*nx) <= 0.5 && fabs(t*ny) <= 0.5)
{
Pt.push_back(i);
Pt.push_back(j);
}
}
}
}
cvtColor(img0, img0, CV_GRAY2BGR);//不需要验证时可注释掉
vector<Point> LaserLinePtSet;//输出的点集
for (int k = 0; k<Pt.size() / 2; k++)
{
Point rpt;
rpt.x = Pt[2 * k + 0];
rpt.y = Pt[2 * k + 1];
LaserLinePtSet.push_back(rpt);//将点加入到输出点集集合中
circle(img0, rpt, 1, Scalar(0, 0, 255));
}
//以下部分为验证代码
namedWindow("result", CV_WINDOW_NORMAL);
imshow("result", img0);
imwrite("output.bmp", img0);
return LaserLinePtSet;
}