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楼主 |
发表于 2012-5-6 19:29:51
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【代码】单目摄像机标定程序_分享
以下是我引入实际标定板方格宽度的标定程序，是以我发的帖子的基础修改的，代码如下
如果转载，请注明出处http://blog.csdn.net/guvcolie/article/details/7628406
#include "stdafx.h"
#include "cv.h"
#include "highgui.h"
#include <string>
#include <iostream>
using namespace std;
int main()
{
CvCapture* capture; //摄像头指针
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; //图像指针
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; //文件名后的编号，从1开始，也是截取的图像帧数
char filename[20]=""; //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(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); //若您的是1.0版本，如果报错请修改为cvReleaseCapture(&capture)，或将此句加在cvReleaseImage(&frame);后
cvDestroyWindow("摄像机帧截取窗口");
IplImage * show; //RePlay图像指针
cvNamedWindow("RePlay",1);
int number_image_copy=number_image; //复制图像帧数
CvSize board_size=cvSize(7,7); //标定板角点数
CvSize2D32f square_size=cvSize2D32f(18.2,18.2); //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=0; //存储成功找到标定板上所有角点的图像帧数
int a=1; //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,2,CV_32FC1); //存储角点的图像坐标的矩阵
CvMat * object_points=cvCreateMat(number_image*total_per_image,3,CV_32FC1); //存储角点的三维坐标的矩阵
CvMat * point_counts=cvCreateMat(number_image,1,CV_32SC1); //存储每帧图像的识别的角点数
CvMat * intrinsic_matrix=cvCreateMat(3,3,CV_32FC1); //内参数矩阵
CvMat * distortion_coeffs=cvCreateMat(5,1,CV_32FC1); //畸变系数
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){ //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",1);
cvShowImage("RePlay",show);
cvWaitKey(0);
}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",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; //计算存储相应坐标数据的步长
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/board_width)*square_length);
CV_MAT_ELEM(*object_points,float,i,1)=(float)((j%board_width)*square_height);
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;
}
以下是一个同学用我的这个程序标定的图片，他的是广角相机，左上角可能因为安装、质量原因，比其他角的畸变较大，但整体效果可以
如果这个程序有什么问题或者疑问，请回帖，我会尽快予以回复！  |
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楼主: guvcolie
发表于 2012-5-4 12:56:53
