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OpenCV 最小二乘法拟合平面

2022-05-25 16:02:03  阅读:219  来源: 互联网

标签:vector ncols int OpenCV plane dx 拟合 data 乘法


本文主要验证了博客上的最小二乘法拟合平面的。与 用matlab拟合出来的平面计算的点到直线的距离是一样的,而且系数也是一样的。说明了本方法的可行性。
matlab中公式为z = c + ax +by
oepncv中公式为Ax+By+Cz=D 将opencv中公式换算成matlab的公式,系数是一样的。

平面公式为:Ax+By+Cz=D

//对应的方程:Ax+By+Cz=D 其中 A = plane12[0], B = plane12[1], C = plane12[2], D = plane12[3],这是要注意的方程的表示
//float plane12[4] = { 0 };//定义用来储存平面参数的数组,分别对应ABCD

拟合平面

 1 void cvFitPlane(vector<float>dx, vector<float>dy, vector<float>dz, float* plane) {
 2 
 3     //直线方程为:
 4     //构建点集cvmat
 5     CvMat* points = cvCreateMat(dx.size(), 3, CV_32FC1);
 6     int nnum = 96;
 7     for (int i = 0; i < dx.size(); ++i)
 8     {
 9         points->data.fl[i * 3 + 0] = dx[i];//矩阵的值进行初始化   X的坐标值  
10         points->data.fl[i * 3 + 1] = dy[i];//  Y的坐标值  
11         points->data.fl[i * 3 + 2] = dz[i]; //  Z的坐标值
12 
13     }
14 
15      Estimate geometric centroid.  
16     int nrows = points->rows;
17     int ncols = points->cols;    
18     int type = points->type;
19     CvMat* centroid = cvCreateMat(1, ncols, type);
20     cvSet(centroid, cvScalar(0));
21     for (int c = 0; c < ncols; c++) {
22         for (int r = 0; r < nrows; r++)
23         {
24             centroid->data.fl[c] += points->data.fl[ncols*r + c];
25         }
26         centroid->data.fl[c] /= nrows;
27     }
28     // Subtract geometric centroid from each point.  
29     CvMat* points2 = cvCreateMat(nrows, ncols, type);
30     for (int r = 0; r < nrows; r++)
31         for (int c = 0; c < ncols; c++)
32             points2->data.fl[ncols*r + c] = points->data.fl[ncols*r + c] - centroid->data.fl[c];
33     // Evaluate SVD of covariance matrix.  
34     CvMat* A = cvCreateMat(ncols, ncols, type);
35     CvMat* W = cvCreateMat(ncols, ncols, type);
36     CvMat* V = cvCreateMat(ncols, ncols, type);
37 
38     cvGEMM(points2, points, 1, NULL, 0, A, CV_GEMM_A_T);
39     cvSVD(A, W, NULL, V, CV_SVD_V_T);
40 
41     // Assign plane coefficients by singular vector corresponding to smallest singular value.  
42     plane[ncols] = 0;
43     for (int c = 0; c < ncols; c++) {
44         plane[c] = V->data.fl[ncols*(ncols - 1) + c];
45         plane[ncols] += plane[c] * centroid->data.fl[c];
46     }
47     // Release allocated resources.  
48     cvReleaseMat(&points);
49     cvReleaseMat(&centroid);
50     cvReleaseMat(&points2);
51     cvReleaseMat(&A);
52     cvReleaseMat(&W);
53     cvReleaseMat(&V);
54 }

计算点到平面的距离

 1 //计算点到平面的距离
 2 //Ax+By+Cz=D
 3 //|点(a,b,c) 到平面bai Ax+By+Cz=D的距离du
 4 
 5 //= | A * a + B * b + C * c - D| /√(A ^ 2 + B ^ 2 + C ^ 2)
 6 void calculateDist(vector<float>dx, vector<float>dy, vector<float>dz, float* plane, vector<float> &dist)
 7 {
 8     for (int i = 0; i < dx.size(); i++)
 9     {
10         float ds = fabs(plane[0] * dx[i] + plane[1] * dy[i] + plane[2] * dz[i] - plane[3]);
11         float dfen = sqrt(plane[0] * plane[0] + plane[1] * plane[1] + plane[2] * plane[2]);
12         if (!(dfen > -0.00001 && dfen < -0.00001))
13         {
14             float ddist = ds / dfen;
15             dist.push_back(ddist);
16         }        
17     }
18 }

测试流程

从文件中读取数据,然后计算拟合平面,计算点到平面的距离,并输出到csv文件中
数据格式为:
一行中代表xyz

1 -53.883533,55.133049,895.801941
2 -40.928612,32.402653,897.237793
3 -21.391739,50.161041,899.748901
4 2.107507,62.850151,902.479065
5 3.594930,37.490810,902.427490

具体代码为:

 1 fstream fs;
 2     fs.open("E:\\wokspace\\PROJECT\\ThirdTrailInspection\\matlab\\dResult.txt");
 3     if (!fs.is_open())
 4     {
 5         return;
 6     }
 7     vector<float> dx;
 8     vector<float> dy;
 9     vector<float> dz;
10     int i = 0;
11     string buff;
12     while (getline(fs, buff))//是否到文件结bai尾
13     {
14         int nfist = buff.find_first_of(',');
15         int nLast = buff.find_last_of(',');
16         string st1 = buff.substr(0, nfist);
17         string st2 = buff.substr(nfist + 1, nLast - nfist - 1);
18         string st3 =(buff.substr(nLast + 1));
19         dx.push_back(stof(buff.substr(0, nfist)));
20         dy.push_back(stof(buff.substr(nfist + 1, nLast - nfist - 1)));
21         dz.push_back(stof(buff.substr(nLast + 1)));        
22     }
23     fs.close();
24 
25 
26     //代入最小二乘算法中
27     float plane[4] = { 0 };
28     vector<float> dx1;
29     vector<float> dy1;
30     vector<float> dz1;
31     dx1.assign(dx.begin(), dx.begin() + 96);
32     dy1.assign(dy.begin(), dy.begin() + 96);
33     dz1.assign(dz.begin(), dz.begin() + 96);
34     cvFitPlane(dx1, dy1, dz1,  plane);
35     vector<float> dist;
36     calculateDist(dx, dy, dz, plane, dist);
37     fstream fws("e://de.csv", fstream::in | fstream::out | fstream::trunc);
38     for (int i = 0; i < dist.size(); i++)
39     {
40         fws << dist[i] <<"\r";
41     }
42     fws.close();

对应的matlab代码

 1 clc;
 2 close all;
 3 clear all;
 4 %https://www.ilovematlab.cn/thread-220252-1-1.html
 5 
 6 data = importdata('E:\wokspace\PROJECT\ThirdTrailInspection\matlab\dResult.txt');
 7 x = data(1:96, 1);
 8 y = data(1:96, 2);
 9 z = data(1:96, 3);
10 % x = data(113:192, 1);
11 % y = data(113:192, 2);
12 % z = data(113:192, 3);
13 scatter3(x, y,z, 'r');%画点  散点图
14 hold on;
15 X = [ones(length(x),1) x y];
16 [b,bint,r,rint,stats] = regress(z,X,95);
17 
18 % 图形绘制
19 xfit = min(x):0.1:max(x);
20 yfit = min(y):0.1:max(y);
21 [XFIT,YFIT]= meshgrid (xfit,yfit);%用于生成网格采样点
22 ZFIT = b(1) + b(2) * XFIT + b(3) * YFIT;
23 mesh(XFIT,YFIT,ZFIT);
24 
25 %%测试结果
26 %data = importdata('C:\Users\apr_z\Desktop\dResult.txt');
27 xx = data(:, 1);
28 yy = data(:, 2);
29 zz = data(:, 3);
30 [row, col] = size(xx);%求矩阵的行数和列数
31 dist = ones(row, 1);
32 for i = 1: row
33     dist(i) = abs(b(2) * xx(i) + b(3) * yy(i)  - zz(i) + b(1)) / sqrt(b(2)* b(2) + b(3)*b(3) + 1 );
34 end
35 xlswrite('C:\Users\apr_z\Desktop\AnalyzeResult.xlsx', dist);

小结:
vector 复制某一些数据时: dx1.assign(dx.begin(), dx.begin() + 96);

vector容器 追加其他容器的内容,使用insert
pt3DList.insert(pt3DList.end(), vc.begin(), vc.end());

用此平面拟合的计算 点到直线的距离 与 用matlab计算出来的点到直线的距离是一模一样的。

标签:vector,ncols,int,OpenCV,plane,dx,拟合,data,乘法
来源: https://www.cnblogs.com/ybqjymy/p/16309568.html

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