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：图像拼接融合、图像识别 联系方式：jsxyhelu@foxmail.com
