生活随笔
收集整理的这篇文章主要介绍了
相机标定获得内参矩阵及其他参数
小编觉得挺不错的,现在分享给大家,帮大家做个参考.
csdn博客推荐：http://blog.csdn.net/chenyusiyuan/article/details/5963256
理论方面和单目标定opencv代码网址：
http://pan.baidu.com/s/1cFRWg2
下面为转载的一部分
我自己写了一个摄像机标定程序，核心算法参照learning opencv，但是那个程序要从命令行预先输入参数，且标定图片要预先准备好，我觉得不太好，我就自己写了一个，跟大家分享下。
若有纰漏，希望大家指正！
[cpp] view plaincopy
#include <string> #include <iostream> #include <cv.h> #include <highgui.h> #pragma comment(lib, "ml.lib") #pragma comment(lib, "cv.lib") #pragma comment(lib, "cvaux.lib") #pragma comment(lib, "cvcam.lib") #pragma comment(lib, "cxcore.lib") #pragma comment(lib, "cxts.lib") #pragma comment(lib, "highgui.lib") #pragma comment(lib, "cvhaartraining.lib") using namespace std; int main() { int cube_length=7; CvCapture* capture; capture=cvCreateCameraCapture(0); if(capture==0) { printf("无法捕获摄像头设备！\n\n"); return 0; } else { printf("捕获摄像头设备成功！！\n\n"); } IplImage* frame = NULL; cvNamedWindow("摄像机帧截取窗口",1); printf("按“C”键截取当前帧并保存为标定图片...\n按“Q”键退出截取帧过程...\n\n"); int number_image=1; char *str1; str1=".jpg"; char filename[20]=""; while(true) { frame=cvQueryFrame(capture); if(!frame) break; cvShowImage("摄像机帧截取窗口",frame); if(cvWaitKey(10)=='c') { sprintf_s (filename,"%d.jpg",number_image); cvSaveImage(filename,frame); cout<<"成功获取当前帧，并以文件名"<<filename<<"保存...\n\n"; printf("按“C”键截取当前帧并保存为标定图片...\n按“Q”键退出截取帧过程...\n\n"); number_image++; } else if(cvWaitKey(10)=='q') { printf("截取图像帧过程完成...\n\n"); cout<<"共成功截取"<<--number_image<<"帧图像！！\n\n"; break; } } cvReleaseImage(&frame); cvDestroyWindow("摄像机帧截取窗口"); IplImage * show; cvNamedWindow("RePlay",1); int a=1; int number_image_copy = number_image; CvSize board_size=cvSize(7,7); int board_width=board_size.width; int board_height=board_size.height; int total_per_image=board_width*board_height; CvPoint2D32f * image_points_buf = new CvPoint2D32f[total_per_image]; CvMat * image_points=cvCreateMat(number_image*total_per_image,2,CV_32FC1); CvMat * object_points=cvCreateMat(number_image*total_per_image,3,CV_32FC1); CvMat * point_counts=cvCreateMat(number_image,1,CV_32SC1); CvMat * intrinsic_matrix=cvCreateMat(3,3,CV_32FC1); CvMat * distortion_coeffs=cvCreateMat(5,1,CV_32FC1); int count; int found; int step; int successes=0; while(a<=number_image_copy) { sprintf_s (filename,"%d.jpg",a); show=cvLoadImage(filename,-1); found=cvFindChessboardCorners(show,board_size,image_points_buf,&count, CV_CALIB_CB_ADAPTIVE_THRESH|CV_CALIB_CB_FILTER_QUADS); if(found==0) { cout<<"第"<<a<<"帧图片无法找到棋盘格所有角点!\n\n"; cvNamedWindow("RePlay",1); cvShowImage("RePlay",show); cvWaitKey(0); } else { cout<<"第"<<a<<"帧图像成功获得"<<count<<"个角点...\n"; cvNamedWindow("RePlay",1); IplImage * gray_image= cvCreateImage(cvGetSize(show),8,1); cvCvtColor(show,gray_image,CV_BGR2GRAY); cout<<"获取源图像灰度图过程完成...\n"; cvFindCornerSubPix(gray_image,image_points_buf,count,cvSize(11,11),cvSize(-1,-1), cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,0.1)); cout<<"灰度图亚像素化过程完成...\n"; cvDrawChessboardCorners(show,board_size,image_points_buf,count,found); cout<<"在源图像上绘制角点过程完成...\n\n"; cvShowImage("RePlay",show); cvWaitKey(0); } if(total_per_image==count) { step=successes*total_per_image; for(int i=step,j=0;j<total_per_image;++i,++j) { CV_MAT_ELEM(*image_points,float,i,0)=image_points_buf[j].x; CV_MAT_ELEM(*image_points,float,i,1)=image_points_buf[j].y; CV_MAT_ELEM(*object_points,float,i,0)=(float)(j/cube_length); CV_MAT_ELEM(*object_points,float,i,1)=(float)(j%cube_length); CV_MAT_ELEM(*object_points,float,i,2)=0.0f; } CV_MAT_ELEM(*point_counts,int,successes,0)=total_per_image; successes++; } a++; } cvReleaseImage(&show); cvDestroyWindow("RePlay"); cout<<"*********************************************\n"; cout<<number_image<<"帧图片中，标定成功的图片为"<<successes<<"帧...\n"; cout<<number_image<<"帧图片中，标定失败的图片为"<<number_image-successes<<"帧...\n\n"; cout<<"*********************************************\n\n"; cout<<"按任意键开始计算摄像机内参数...\n\n"; CvCapture* capture1; capture1=cvCreateCameraCapture(0); IplImage * show_colie; show_colie=cvQueryFrame(capture1); CvMat * object_points2=cvCreateMat(successes*total_per_image,3,CV_32FC1); CvMat * image_points2=cvCreateMat(successes*total_per_image,2,CV_32FC1); CvMat * point_counts2=cvCreateMat(successes,1,CV_32SC1); for(int i=0;i<successes*total_per_image;++i) { CV_MAT_ELEM(*image_points2,float,i,0)=CV_MAT_ELEM(*image_points,float,i,0); CV_MAT_ELEM(*image_points2,float,i,1)=CV_MAT_ELEM(*image_points,float,i,1); CV_MAT_ELEM(*object_points2,float,i,0)=CV_MAT_ELEM(*object_points,float,i,0); CV_MAT_ELEM(*object_points2,float,i,1)=CV_MAT_ELEM(*object_points,float,i,1); CV_MAT_ELEM(*object_points2,float,i,2)=CV_MAT_ELEM(*object_points,float,i,2); } for(int i=0;i<successes;++i) { CV_MAT_ELEM(*point_counts2,int,i,0)=CV_MAT_ELEM(*point_counts,int,i,0); } cvReleaseMat(&object_points); cvReleaseMat(&image_points); cvReleaseMat(&point_counts); CV_MAT_ELEM(*intrinsic_matrix,float,0,0)=1.0f; CV_MAT_ELEM(*intrinsic_matrix,float,1,1)=1.0f; cvCalibrateCamera2(object_points2,image_points2,point_counts2,cvGetSize(show_colie), intrinsic_matrix,distortion_coeffs,NULL,NULL,0); cout<<"摄像机内参数矩阵为：\n"; cout<<CV_MAT_ELEM(*intrinsic_matrix,float,0,0)<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,0,1) <<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,0,2) <<"\n\n"; cout<<CV_MAT_ELEM(*intrinsic_matrix,float,1,0)<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,1,1) <<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,1,2) <<"\n\n"; cout<<CV_MAT_ELEM(*intrinsic_matrix,float,2,0)<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,2,1) <<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,2,2) <<"\n\n"; cout<<"畸变系数矩阵为：\n"; cout<<CV_MAT_ELEM(*distortion_coeffs,float,0,0)<<" "<<CV_MAT_ELEM(*distortion_coeffs,float,1,0) <<" "<<CV_MAT_ELEM(*distortion_coeffs,float,2,0) <<" "<<CV_MAT_ELEM(*distortion_coeffs,float,3,0) <<" "<<CV_MAT_ELEM(*distortion_coeffs,float,4,0) <<"\n\n"; cvSave("Intrinsics.xml",intrinsic_matrix); cvSave("Distortion.xml",distortion_coeffs); cout<<"摄像机矩阵、畸变系数向量已经分别存储在名为Intrinsics.xml、Distortion.xml文档中\n\n"; CvMat * intrinsic=(CvMat *)cvLoad("Intrinsics.xml"); CvMat * distortion=(CvMat *)cvLoad("Distortion.xml"); IplImage * mapx=cvCreateImage(cvGetSize(show_colie),IPL_DEPTH_32F,1); IplImage * mapy=cvCreateImage(cvGetSize(show_colie),IPL_DEPTH_32F,1); cvInitUndistortMap(intrinsic,distortion,mapx,mapy); cvNamedWindow("原始图像",1); cvNamedWindow("非畸变图像",1); cout<<"按‘E’键退出显示...\n\n"; while(show_colie) { IplImage * clone=cvCloneImage(show_colie); cvShowImage("原始图像",show_colie); cvRemap(clone,show_colie,mapx,mapy); cvReleaseImage(&clone); cvShowImage("非畸变图像",show_colie); if(cvWaitKey(10)=='e') { break; } show_colie=cvQueryFrame(capture1); } return 0; }
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