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对自主标定的实现

//重新整理的比较清楚的opencv框架

#include "stdafx.h"

 

#include <cv.h>

#include <highgui.h>

#include <iostream>

 

using namespace std;

using namespace cv;

 

 

 

int _tmain(int argc, _TCHAR* argv[])

{      

         Mat lastWarpMatrix;Mat warpMatrix;

         //读取数据

         for (int i =2;i<=13;i++)//执行全部文件的遍历

         {

         char strimg[50];

    sprintf(strimg,"image_%d.jpg",i);

         cv::Mat src= cv::imread(strimg,0);

         if (!src.data)

                   return 0;  

   // pyrDown(src,src);

         Mat edge;Mat edgesobel;Mat edgetresh;

    vector<std::vector<cv::Point>>contours;

         threshold(src,edgetresh,22,255,cv::THRESH_BINARY);

    imshow("edgetresh",edgetresh);

         findContours(edgetresh,contours,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_NONE);

         Mat result(src.size(),CV_8U,Scalar(255));

         src.copyTo(result);

         //寻找最大contours

         int cmax = 0;

         vector<vector<Point>>::const_iterator itc = contours.begin();

             //在这种循环下面,最后一个就是最大的数据

                   while(itc!=contours.end())

                   {

                            if (itc->size()>cmax)

                            {

                                     cmax = itc->size();

                                     ++itc;

                            }

                            else

                            {

                                     itc = contours.erase(itc);

                            }

                   }

         if (contours.size() <= 0)//如果没有数据

         {

                   return 0;//error

         }

    drawContours(result,contours,-1,Scalar(255),1);

         //获得最大外边距的点序列

         std::vector<cv::Point> thiscount = contours[contours.size()-1];

         Point lt =thiscount[0];Point ltEX  =thiscount[0];//前面为原始,后面为修正

         Point rt =thiscount[0];Point rtEX  =thiscount[0];

         Point ld =thiscount[0];Point ldEX  =thiscount[0];

         Point rd =thiscount[0];Point rdEX  =thiscount[0];

   for (int i = 0;i<thiscount.size();i++)

   {

            Point thispoint =thiscount[i];

            //左上角,往往这个点也就是第一个点

          if (thispoint.x<lt.x & thispoint.y<lt.y )

          {

                    lt = thispoint;

          }

            //右上角

         else if (thispoint.x>=rt.x & thispoint.y<5)

          {

                    rt = thispoint;

          }

           //右下角 这里就是找最大的

           else if (thispoint.x>rd.x /*& thispoint.y>100*/)

           {

                     rd = thispoint;

           }//左下角 这里就是找最小的

           else if (thispoint.x<ld.x/* && thispoint.y >100*/)

           {

                     ld = thispoint;

           }

          

   }

 

                   if ((ld.y == lt.y)|(rt.y==rd.y) )

                   {

                            printf("err in %d",i);

                   }

                   else

                   {

                            //修正,根据直线的斜率

                            ltEX.y = 0;rt.y = 0;rdEX.y = result.rows;ldEX.y = result.rows;

                            ltEX.x = (lt.x-ld.x)*lt.y/(ld.y-lt.y)+lt.x;

                            ldEX.x = ld.x-(ld.y-result.rows)*(lt.x-ld.x)/(lt.y-ld.y);

                            rtEX.x = rt.x+(rd.x-rt.x)*rt.y/(rt.y-rd.y)-13;//由于打光问题,进行修正。这样的修正是否可以将接口提取出来

                            rdEX.x = rd.x -(rt.x-rd.x)*(rd.y-result.rows)/(rt.y-rd.y);

                            cv::circle(result,ltEX,10,Scalar(255));

                            cv::circle(result,ldEX,10,Scalar(255));

                            cv::circle(result,rtEX,10,Scalar(255));

                            cv::circle(result,rdEX,10,Scalar(255));

                       

                            printf("ltex %d %d\n",ltEX.x,ltEX.y);

                            printf("rtex %d %d\n",rtEX.x,rtEX.y);

                            printf("ldex %d %d\n",ldEX.x,ldEX.y);

                            printf("rdex %d %d\n",rdEX.x,rdEX.y);

                            if (ldEX.x<0)//问题出现

                            {

                                    //当前错误,尝试lastwarp

                                 if (lastWarpMatrix.rows == 0)

                                 {

                                           return 0 ;//TODO这个问题现在还没有解决。

                                 }

                                 else//存在lastwarp

                                 {

                                           lastWarpMatrix.copyTo(warpMatrix);

                                 }

                            }

                            else

                            {

                                     //warpperspective 透视矫正

                                     Point2f src_vertices[4];

                                     src_vertices[0] = ltEX;

                                     src_vertices[1] = rtEX;

                                     src_vertices[2] = ldEX;

                                     src_vertices[3] = rdEX;

 

                                     Point2f dst_vertices[4]; //边界略微留有黑边

                                     dst_vertices[0] = Point(0+20, 0);

                                     dst_vertices[1] = Point(result.cols-20,0);

                                     dst_vertices[2] = Point(0+20,result.rows);

                                     dst_vertices[3] = Point(result.cols-20,result.rows);

 

                                     warpMatrix = getPerspectiveTransform(src_vertices, dst_vertices);

                                     warpMatrix.copyTo(lastWarpMatrix);

                            }

                            cv::Mat rotated;

                            warpPerspective(src, rotated, warpMatrix, rotated.size(), INTER_LINEAR, BORDER_CONSTANT);

                            //cv::line(result,lt,ld,Scalar(255));cv::line(result,rt,rd,Scalar(255));

                            imshow("result",result);

                            imshow("rotated",rotated);

                            char rstr[50];

                            sprintf(rstr,"adjust%d.jpg",i);

                            imwrite(rstr,rotated);

                   }

          

            cv::waitKey();

         }

         return 0;

}

 

 

 

 

目前方向:图像处理,人工智能
posted @ 2014-07-31 21:07  jsxyhelu  阅读(669)  评论(0编辑  收藏  举报