C++ findChessboardCorners 校准图像失败
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原文地址: http://stackoverflow.com/questions/17665912/
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findChessboardCorners fails for calibration image
提问by laurenelizabeth
I am trying to get OpenCV 2.4.5 to recognize a checkerboard pattern from my webcam. I couldn't get that working, so I decided to try to get it working just using a "perfect" image:
我试图让 OpenCV 2.4.5 从我的网络摄像头识别棋盘图案。我无法让它工作，所以我决定尝试使用“完美”图像来让它工作：
but it still won't work--patternFound returns false every time. Does anyone have any idea what I'm doing wrong?
但它仍然不起作用——patternFound 每次都返回false。有谁知道我做错了什么？
#include <stdio.h>
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/calib3d/calib3d.hpp>
#include <opencv2/highgui/highgui.hpp>
using namespace cv;
using namespace std;
int main(){
Size patternsize(8,8); //number of centers
Mat frame = imread("perfect.png"); //source image
vector<Point2f> centers; //this will be filled by the detected centers
bool patternfound = findChessboardCorners(frame,patternsize,centers);
cout<<patternfound<<endl;
drawChessboardCorners(frame, patternsize, Mat(centers), patternfound);
cvNamedWindow("window");
while(1){
imshow("window",frame);
cvWaitKey(33);
}
}
回答by laurenelizabeth
Through trial and error, I realized that patternsize should be 7x7 since it is counting internal corners. This parameter has to be exact--8x8 won't work, but neither will anything less than 7x7.
通过反复试验，我意识到 patternsize 应该是 7x7，因为它计算内角。此参数必须准确--8x8 不起作用，但任何小于 7x7 的参数也不起作用。
回答by Desai
Instead of using
而不是使用
Size patternsize(8,8);
use
用
Size patternsize(7,7);
回答by CTZStef
Width and height of the chessboard can't be of the same length, i.e. it needs to be assymetric. This might be the source of your problem. Hereis a very good tutorial about camera calibration with OpenCV.
棋盘的宽度和高度不能相同，即必须不对称。这可能是您问题的根源。 这是一个关于使用 OpenCV 校准相机的非常好的教程。
Just below is the code I use for my calibration (tested and fully functional, HOWEVER I call it in some processing thread of my own, you should call it in your processing loop or whatever you are using to catch your frames) :
下面是我用于校准的代码（经过测试且功能齐全，但是我在自己的某个处理线程中调用它，您应该在处理循环或用于捕获帧的任何东西中调用它）：
void MyCalibration::execute(IplImage* in, bool debug)
{
const int CHESSBOARD_WIDTH = 8;
const int CHESSBOARD_HEIGHT = 5;
const int CHESSBOARD_INTERSECTION_COUNT = CHESSBOARD_WIDTH * CHESSBOARD_HEIGHT;
//const bool DO_CALIBRATION = ((BoolProperty*)getProperty("DoCalibration"))->getValue();
if(in->nChannels == 1)
cvCopy(in,gray_image);
else
cvCvtColor(in,gray_image,CV_BGR2GRAY);
int corner_count;
CvPoint2D32f* corners = new CvPoint2D32f[CHESSBOARD_INTERSECTION_COUNT];
int wasChessboardFound = cvFindChessboardCorners(gray_image, cvSize(CHESSBOARD_WIDTH, CHESSBOARD_HEIGHT), corners, &corner_count);
if(wasChessboardFound) {
// Refine the found corners
cvFindCornerSubPix(gray_image, corners, corner_count, cvSize(5, 5), cvSize(-1, -1), cvTermCriteria(CV_TERMCRIT_ITER, 100, 0.1));
// Add the corners to the array of calibration points
calibrationPoints.push_back(corners);
cvDrawChessboardCorners(in, cvSize(CHESSBOARD_WIDTH, CHESSBOARD_HEIGHT), corners, corner_count, wasChessboardFound);
}
}
Just in case you wondered about the class members, here is my class (IplImage was still around at the time I wrote it) :
以防万一你想知道班级成员，这是我的班级（在我写它的时候 IplImage 还在附近）：
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv/cv.h>
class MyCalibration
{
private:
std::vector<CvPoint2D32f*> calibrationPoints;
IplImage *gray_image;
public:
MyCalibration(IplImage* in);
void execute(IplImage* in, bool debug=false);
~MyCalibration(void);
};
And finally the constructor :
最后是构造函数：
MyCalibration::MyCalibration(IplImage* in)
{
gray_image = cvCreateImage(cvSize(in->width,in->height),8,1);
}
