处理相机畸变与偏移矫正（附标定工具）

相机畸变处理与偏移矫正

• 环境： C++ QT Opencv

1. 这里已经使用MatLab工具箱，得到了畸变参数xml文件

    Mat img = imread(imgName.toStdString());
       if (img.empty()){
           qDebug() <<"[LOG]preprocess read img is fail."<< imgName;
       }
       imwrite("img_原图.jpg",img);
       // 读取畸变参数
       FileStorage file_xml("data.xml", FileStorage::READ);
       if (!file_xml.isOpened()){
           qDebug()<<"[LOG]Open out_camera_data.xml is fail!";
       }
       Mat camera_matrix;
       Mat distortion_coefficients;
       file_xml["camera_matrix"] >> camera_matrix;
       file_xml["distortion_coefficients"] >> distortion_coefficients;
       file_xml.release();
       // 去畸变
       undistort(img.clone(),img,camera_matrix, distortion_coefficients);
       // 水平翻转
       flip(img.clone(),img,-1);
   

• 原图：

• 畸变矫正后：

2. 偏转矫正（二维码偏转矫正）

    if (all_rect.empty()){
        Mat gray_img;
        cvtColor(img,gray_img,CV_BGR2GRAY);
		// 二值
        threshold(gray_img.clone(),gray_img,0,255,THRESH_BINARY | THRESH_OTSU);
        vector<vector<Point>> contours;
        vector<Vec4i> hierarchy;
        // 找轮廓
        findContours(gray_img, contours, hierarchy, CV_RETR_TREE, CHAIN_APPROX_NONE, Point(0, 0));
       // 寻找三个角点
        for (unsigned int i=0; i<contours.size(); i++){
            if (hierarchy[i][2] != 1){
            	// 是否包含子框
                if (is_father(i, hierarchy)){
                    RotatedRect rotatedRect = minAreaRect(contours[i]);
                    if (rotatedRect.size.width < 30 || rotatedRect.size.height < 30) continue;
                    if (rotatedRect.size.width > 45 || rotatedRect.size.height > 45) continue;
                    Rect rect;
                    rect.x = rotatedRect.center.x;
                    rect.y = rotatedRect.center.y;
                    rect.width = rotatedRect.size.width;
                    rect.height = rotatedRect.size.height;
                    qDebug() << "size: "<< rect.x<< " " << rect.y;
                    all_rect.push_back(rect);
                }
            }
        }

        sort(all_rect.begin(),all_rect.end(),ccmp); //脚点排序
    }
    Point2f src[4]; // 存储四个角点信息
    src[0] = Point(all_rect[0].x - all_rect[0].width/2, all_rect[0].y - all_rect[0].height/2);
    src[1] = Point(all_rect[1].x + all_rect[1].width/2, all_rect[1].y - all_rect[1].height/2);
    src[2] = Point(all_rect[2].x + all_rect[2].width/2, all_rect[2].y + all_rect[2].height/2);
    src[3] = Point(all_rect[0].x - all_rect[0].width/2, all_rect[2].y + all_rect[2].height/2);
//    line(img,src[0],src[1],Scalar(0,255,0),4);
//    line(img,src[1],src[2],Scalar(0,255,0),4);
//    line(img,src[2],src[3],Scalar(0,255,0),4);
//    line(img,src[3],src[0],Scalar(0,255,0),4);

    Point2f dst[4]; // 获取图像变换后位置
    dst[0] = Point(0, 0);
    dst[1] = Point(img.cols, 0);
    dst[2] = Point(img.cols, img.rows);
    dst[3] = Point(0, img.rows);
    Mat M = getPerspectiveTransform(src,dst); //得到变换矩阵
//    Mat rotated;
    warpPerspective(img,result_img,M,img.size()); //opencv 的透视变换
    imwrite("./test_test.jpg",result_img);
}

• 结果图片

【相机标定工具（单目+双目+matlab）】
链接：https://pan.baidu.com/s/1X00PszoMSI7Zi7nXoEOR7w
提取码：qo8r