opencv单目摄像机标定（二）

 // 引入实际标定板方格宽度的标定程序

   #include <string>

   #include <iostream>

   #include <cv.h>

   #include <highgui.h>  

using namespace std;

int main()

{

CvCapture* capture; //摄像头指针

capture=cvCreateCameraCapture();

if(capture==){

printf("无法捕获摄像头设备！\n\n");

return ;

}else{

printf("捕获摄像头设备成功！！\n\n");

}

IplImage* frame; //图像指针

cvNamedWindow("摄像机帧截取窗口",);

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=; //文件名后的编号，从1开始，也是截取的图像帧数

char filename[]=""; //保存文件名的字符串数组

while(true)

{

frame=cvQueryFrame(capture);

if(!frame)

break;

cvShowImage("摄像机帧截取窗口",frame);

if(cvWaitKey()=='c'){

sprintf (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()=='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);

cvReleaseCapture(&capture);

cvDestroyWindow("摄像机帧截取窗口");

IplImage * show; //RePlay图像指针

cvNamedWindow("RePlay",);

int number_image_copy=number_image; //复制图像帧数

CvSize board_size=cvSize(,); //标定板角点数

CvSize2D32f square_size=cvSize2D32f(18.2,18.2); //cvSize2D32f( double width, double height );假设我的每个标定方格长宽都是1.82厘米

float square_length=square_size.width; //方格长度

float square_height=square_size.height; //方格高度

int board_width=board_size.width; //每行角点数

int board_height=board_size.height; //每列角点数

int total_per_image=board_width*board_height; //每张图片角点总数

int count; //存储每帧图像中实际识别的角点数

int found; //识别标定板角点的标志位

int step; //存储步长，step=successes*total_per_image;

int successes=; //存储成功找到标定板上所有角点的图像帧数

int a=; //临时变量，表示在操作第a帧图像

CvPoint2D32f * image_points_buf = new CvPoint2D32f[total_per_image]; //存储角点图像坐标的数组

CvMat * image_points=cvCreateMat(number_image*total_per_image,,CV_32FC1); //存储角点的图像坐标的矩阵

CvMat * object_points=cvCreateMat(number_image*total_per_image,,CV_32FC1); //存储角点的三维坐标的矩阵

CvMat * point_counts=cvCreateMat(number_image,,CV_32SC1); //存储每帧图像的识别的角点数

CvMat * intrinsic_matrix=cvCreateMat(,,CV_32FC1); //内参数矩阵

CvMat * distortion_coeffs=cvCreateMat(,,CV_32FC1); //畸变系数

while(a<=number_image_copy){

sprintf (filename,"%d.jpg",a);

show=cvLoadImage(filename,-);

found=cvFindChessboardCorners(show,board_size,image_points_buf,&count,

CV_CALIB_CB_ADAPTIVE_THRESH|CV_CALIB_CB_FILTER_QUADS);

if(found==){ //如果没找到标定板角点时

cout<<"第"<<a<<"帧图片无法找到棋盘格所有角点!\n\n";

cvNamedWindow("RePlay",);

cvShowImage("RePlay",show);

cvWaitKey();

}else{ //找到标定板角点时

cout<<"第"<<a<<"帧图像成功获得"<<count<<"个角点...\n";

cvNamedWindow("RePlay",);

IplImage * gray_image= cvCreateImage(cvGetSize(show),,);

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(,),cvSize(-,-),

cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,,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();

}

if(total_per_image==count){

step=successes*total_per_image; //计算存储相应坐标数据的步长

for(int i=step,j=;j<total_per_image;++i,++j){

CV_MAT_ELEM(*image_points,float,i,)=image_points_buf[j].x;

CV_MAT_ELEM(*image_points,float,i,)=image_points_buf[j].y;

CV_MAT_ELEM(*object_points,float,i,)=(float)((j/board_width)*square_length);

CV_MAT_ELEM(*object_points,float,i,)=(float)((j%board_width)*square_height);

CV_MAT_ELEM(*object_points,float,i,)=0.0f;

}

CV_MAT_ELEM(*point_counts,int,successes,)=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();

IplImage * show_colie;

show_colie=cvQueryFrame(capture1);

CvMat * object_points2=cvCreateMat(successes*total_per_image,,CV_32FC1);

CvMat * image_points2=cvCreateMat(successes*total_per_image,,CV_32FC1);

CvMat * point_counts2=cvCreateMat(successes,,CV_32SC1);

for(int i=;i<successes*total_per_image;++i){

CV_MAT_ELEM(*image_points2,float,i,)=CV_MAT_ELEM(*image_points,float,i,);

CV_MAT_ELEM(*image_points2,float,i,)=CV_MAT_ELEM(*image_points,float,i,);

CV_MAT_ELEM(*object_points2,float,i,)=CV_MAT_ELEM(*object_points,float,i,);

CV_MAT_ELEM(*object_points2,float,i,)=CV_MAT_ELEM(*object_points,float,i,);

CV_MAT_ELEM(*object_points2,float,i,)=CV_MAT_ELEM(*object_points,float,i,);

}

for(int i=;i<successes;++i){

CV_MAT_ELEM(*point_counts2,int,i,)=CV_MAT_ELEM(*point_counts,int,i,);

}

cvReleaseMat(&object_points);

cvReleaseMat(&image_points);

cvReleaseMat(&point_counts);

    //初始化相机内参矩阵

CV_MAT_ELEM(*intrinsic_matrix,float,,)=1.0f;

CV_MAT_ELEM(*intrinsic_matrix,float,,)=1.0f;

 //标定相机的内参矩阵和畸变系数向量

cvCalibrateCamera2(object_points2,image_points2,point_counts2,cvGetSize(show_colie),

intrinsic_matrix,distortion_coeffs,NULL,NULL,);

cout<<"摄像机内参数矩阵为：\n";

cout<<CV_MAT_ELEM(*intrinsic_matrix,float,,)<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,,)

<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,,)

<<"\n\n";

cout<<CV_MAT_ELEM(*intrinsic_matrix,float,,)<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,,)

<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,,)

<<"\n\n";

cout<<CV_MAT_ELEM(*intrinsic_matrix,float,,)<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,,)

<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,,)

<<"\n\n";

cout<<"畸变系数矩阵为：\n";

cout<<CV_MAT_ELEM(*distortion_coeffs,float,,)<<" "<<CV_MAT_ELEM(*distortion_coeffs,float,,)

<<" "<<CV_MAT_ELEM(*distortion_coeffs,float,,)

<<" "<<CV_MAT_ELEM(*distortion_coeffs,float,,)

<<" "<<CV_MAT_ELEM(*distortion_coeffs,float,,)

<<"\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,);

IplImage * mapy=cvCreateImage(cvGetSize(show_colie),IPL_DEPTH_32F,);

cvInitUndistortMap(intrinsic,distortion,mapx,mapy);

cvNamedWindow("原始图像",);

cvNamedWindow("非畸变图像",);

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()=='e'){

break;

}

show_colie=cvQueryFrame(capture1);

}

return ;

}

opencv单目摄像机标定（二）的相关教程结束。