OpenCV单目摄像机标定程序

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！

#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;
}

http://blog.csdn.net/guvcolie/article/details/7454632

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