opencv——pcb上寻找mark点（拟合椭圆的方法）

#include "stdafx.h"
// FitCircle.cpp : 定义控制台应用程序的入口

#include "cv.h"
#include "highgui.h"
#include "cxcore.h"
#include "cvaux.h"
#include <iostream>

using namespace cv;
using namespace std;
void main()
{

    int BasicGlobalThreshold(int*pg,int start,int end);
      CvBox2D findRectContours(IplImage *src);
    IplImage* imgGrey=cvLoadImage("5_000004.bmp",);
    //IplImage* imgGrey=cvLoadImage("28027.jpg",0);
     cvNamedWindow("原始图像");
    //cvShowImage("fa",imgGrey);
    cvShowImage("原始图像",imgGrey);
    double t=(double)getTickCount();

    IplImage* imgBasicGlobalThreshold = cvCreateImage(cvGetSize(imgGrey),IPL_DEPTH_8U,);
    cvCopyImage(imgGrey,imgBasicGlobalThreshold);
    int pg[],i,thre;
    for (i=;i<;i++) pg[i]=;
    for (i=;i<imgBasicGlobalThreshold->imageSize;i++) // 直方图统计
    pg[(BYTE)imgBasicGlobalThreshold->imageData[i]]++;
    thre = BasicGlobalThreshold(pg,,); // 确定阈值
    cout<<"The Threshold of this Image in BasicGlobalThreshold is:"<<thre<<endl;//输出显示阀值

    cvThreshold(imgBasicGlobalThreshold,imgBasicGlobalThreshold,thre,,CV_THRESH_BINARY); // 二值化
    cvNamedWindow("二值图像");
    cvShowImage("二值图像",imgBasicGlobalThreshold);
    CvBox2D box=findRectContours(imgBasicGlobalThreshold);
    t=((double)getTickCount()-t)/getTickFrequency();
    cout<<t<<"  mark点坐标"<<box.center.x<<"\t"<<box.center.y<<endl<<"半径"<<box.size.width<<endl;

    cvWaitKey();

}

  CvBox2D findRectContours(IplImage *src)
{
   CvBox2D box1;
   IplImage* des=cvCreateImage(cvGetSize(src),src->depth,src->nChannels);
    cvZero(des);

    CvMemStorage* memory=cvCreateMemStorage();
    CvSeq* Icontour=NULL;
    CvSeq* maxContour =NULL;

    cvShowImage("原始图像1",src);
    cvFindContours(src,memory,&Icontour, sizeof(CvContour),CV_RETR_LIST,CV_CHAIN_APPROX_SIMPLE,cvPoint(,));
    double area=;
    double maxArea=;

    while(Icontour)
    {
        area=fabs(cvContourArea(Icontour,CV_WHOLE_SEQ));
        //cout<<area<<endl;
        //cvDrawContours(src, Icontour,
        //    CV_RGB(255,255,255), CV_RGB(255, 255,255),
        //    0, 1, 8, cvPoint(0,0));
        //
        if(area> && area<)
        {
            goto l1;

        }
        else
            goto l2;
l1:        CvBox2D box0=cvFitEllipse2(Icontour);
        float a=(float)box0.size.height/(float)box0.size.width;
        //cout<<area<<endl;
        if(fabs(a)<=1.5)
        {
            cvDrawContours(des, Icontour,
            CV_RGB(,,), CV_RGB(, ,), , , , cvPoint(,));
            box1=box0;

         cvDrawCircle(des,cvPoint(box0.center.x,box0.center.y),,cvScalar(,,),,,);
        //cvDrawContours(des,maxContour,cvScalar(0,0,255),cvScalar(0,0,255),1,1,0,cvPoint(0,0));

        }
        //    maxContour = Icontour;

l2:      Icontour =Icontour->h_next;
    }
       cvShowImage("fds",des);

    return box1;

}
/*============================================================================
=  代码内容：基本全局阈值法   迭代法
==============================================================================*/
int BasicGlobalThreshold(int*pg,int start,int end)
{       

    //  基本全局阈值法

    int  i,t,t1,t2,k1,k2;
    double u,u1,u2;
    t=;
    u=;
    for (i=start;i<end;i++)
    {
        t+=pg[i];
        u+=i*pg[i];
    }
    k2=(int) (u/t);                          //  计算此范围灰度的平均值
    do
    {
        k1=k2;
        t1=;
        u1=;
        for (i=start;i<=k1;i++)
        {             //  计算低灰度组的累加和
            t1+=pg[i];
            u1+=i*pg[i];
        }
        t2=t-t1;
        u2=u-u1;
        if (t1)
            u1=u1/t1;                     //  计算低灰度组的平均值
        else
            u1=;
        if (t2)
            u2=u2/t2;                     //  计算高灰度组的平均值
        else
            u2=;
        k2=(int) ((u1+u2)/);                 //  得到新的阈值估计值
    }
    while(k1!=k2);                           //  数据未稳定，继续
    //cout<<"The Threshold of this Image in BasicGlobalThreshold is:"<<k1<<endl;
    return(k1);                              //  返回阈值
}