如何使用opencv从图像中找到标尺位置?

时间:2012-12-10 21:56:53

标签: c++ opencv pixel

我必须使用opencv从图像中找到标尺位置。我能够检测标尺的颜色(绿色)。如何从图像中读取所有像素并获得标尺的上下位置。

void findrulerPosition(cv::Mat image, int indx) {
std::stringstream ss;//create a stringstream
ss << indx;//add number to the stream

cv::Mat hsv;
cvtColor(image, hsv, CV_BGR2HSV);

String filename = OUTPUT_FOLDER + "hsv" + ss.str() + ".png";
imwrite(filename, hsv );

cv::Mat hsvbw;
inRange(hsv, cv::Scalar(30,0,0), cv::Scalar(80, 255, 255), hsvbw);
//inRange(hsv, cv::Scalar(12,255,255), cv::Scalar(23, 245, 255), hsvbw);
   //inRange(image, cv::Scalar(0,64,255), cv::Scalar(0, 207, 255), hsvbw);

filename = OUTPUT_FOLDER + "hsvbw" + ss.str() + ".png";
imwrite(filename, hsvbw );


vector<vector<Point> > contours;
findContours(hsvbw.clone(), contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
cv::Mat dst = Mat::zeros(image.size(), image.type());
drawContours(dst, contours, -1, Scalar::all(255), CV_FILLED);

this->cmpddst &=  dst;
dst &= image;
this->cmpddst &=  image;

filename = OUTPUT_FOLDER + "cmpddst" + ss.str() + ".png";
imwrite(filename, this->cmpddst );


filename = OUTPUT_FOLDER + "dst" + ss.str() + ".png";
imwrite(filename, dst );

}

1 个答案:

答案 0 :(得分:3)

这就是我所做的:

  1. 有点改善你的绿色范围,因为你的绿色范围没有检测到 - 它会检测到许多其他颜色。
  2. 在图像上查找轮廓。
  3. 查找面积大于100的轮廓。
  4. 找出轮廓的低点。
  5. 画出这两点。
  6. Mat src = imread("input.png"), tmp;
    cvtColor(src, tmp, CV_BGR2HSV_FULL);
    inRange(tmp, Scalar(50, 50, 50), Scalar(70, 255, 255), tmp);
    
    vector<vector<Point> > contours;
    findContours(tmp, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
    
    int upY = INT_MAX, lowY = 0, upX, lowX;
    for (int i=0; i<contours.size(); i++)
    {
        if (contourArea(contours[i]) > 100)
        {
            for (int j=0; j<contours[i].size(); j++)
            {
                if (contours[i][j].y > lowY)
                {
                    lowY = contours[i][j].y;
                    lowX = contours[i][j].x;
                }
                if (contours[i][j].y < upY)
                {
                    upY = contours[i][j].y;
                    upX = contours[i][j].x;
                }
            }
    
            cout << "low = (" << lowX << ", " << lowY << ")"<<  endl
                 << "up  = (" << upX << ", " << upY << ")"<<  endl;
            break;
        }
    }
    
    circle(src, Point(lowX, lowY), 3, Scalar(255, 0, 255));
    circle(src, Point(upX, upY), 3, Scalar(255, 0, 255));
    
    imshow("Window", src);
    waitKey();
    

    结果如下:

    enter image description here