在OpenCV中检测轮廓之间的虚线

今天有点棘手，但绝对可行，我认为我走在正确的轨道上。我在试着检测图像中的虚线。我通过寻找一对最适合的轮廓来做到这一点，它们的斜率也与彼此产生的角度一致。参见下面的代码块示例:

//Get canny mat
Mat frame, framegray, detectededges, dummyimg, cannyedges;
cvtColor(frame, framegray, CV_BGR2GRAY);
blur(framegray, detectededges, Size(3,3));
double otsu_thresh_val = cv::threshold(detectededges, dummyimg,0, 255, CV_THRESH_BINARY | CV_THRESH_OTSU);
cv::Canny( detectededges, cannyedges, otsu_thresh_val*0.5, otsu_thresh_val );
//
Scalar color(255,255,0,255);
//Find contours
vector<vector<Point>> contours;
vector<Vec4i> hierarchy;
findContours(cannyedges,contours,hierarchy,CV_RETR_CCOMP,CV_CHAIN_APPROX_SIMPLE);
double contourlength = arcLength(contours[idx], false);
vector<Vec4f> vectorofbestfits;
//Find dotted lines
for (vector<Point> contour : contours){
    //Some filtering
    if ((contourlength > 70.0) && (contours[idx].size() > 5)){
        Vec4f bestfitline;
        fitLine(contour, bestfitline,CV_DIST_L2,0,0.01,0.01);
        vectorofbestfits.push_back(bestfitline);
    }
}
float mtol = 0.05;
for (Vec4f veci : vectorofbestfits){
    float mi = veci[1]/veci[0];
    for (Vec4f vecj : vectorofbestfits){
        float mj = vecj[1]/vecj[0];
        double length = cv::norm(Mat(Point(veci[2],veci[3])),Mat(Point(vecj[2],vecj[3])));
        if (length < 30){
            continue;
        }
        float mk = (veci[3]-vecj[3])/(veci[2]-vecj[2]);
        mi = abs(mi);
        mj = abs(mj);
        mk = abs(mk);
        float mij = abs(mi - mj);
        float mjk = abs(mj - mk);
        float mki = abs(mk - mi);
        if ((mij < mtol) && (mjk < mtol) && (mki < mtol)){
            line(frame,Point(veci[2],veci[3]),Point(vecj[2],vecj[3]),color,2);
        }
    }
}

的方法是:1)创建最适合轮廓线的数组2)遍历数组，得到直线斜率3)重新遍历数组，每隔一条线求斜率4)计算两条线中心形成的直线的斜率5)将所有3个斜率相互比较，并使用容差值

下面的代码从我的图像中生成了大量的行，但是它们没有一个碰到明显的虚线。我觉得斜率的计算有问题。现在它是如此无效，我需要创建一些图像和测试，而不是与现实世界的图形工作。有什么跳出来的吗?

同样，下面的代码计算量相当大，应用程序用于视频解释和帧率是至关重要的，所以任何提高性能的建议都是值得赞赏的。

查找匹配如下:图片

下面是一些更清晰的代码。我也意识到在找到差异之前取斜率的绝对值没有任何意义，只是创建了一堆匹配的偶然轮廓。我需要再玩一些，看看是否有帮助:

//Get canny mat
Mat frame, framegray, detectededges, dummyimg, cannyedges;
cvtColor(frame, framegray, CV_BGR2GRAY);
blur(framegray, detectededges, Size(3,3));
double otsu_thresh_val = cv::threshold(detectededges, dummyimg,0, 255,
    CV_THRESH_BINARY | CV_THRESH_OTSU);
cv::Canny( detectededges, cannyedges, otsu_thresh_val*0.5, otsu_thresh_val );
//Set color for Lines
Scalar color(255,255,0,255);
//Find contours
vector<vector<Point>> contours;
vector<Vec4i> hierarchy;
findContours(cannyedges,contours,hierarchy,CV_RETR_CCOMP,CV_CHAIN_APPROX_SIMPLE);
double contourlength = arcLength(contours[idx], false);
vector<Vec4f> arrayofbestfits;
//Create an array of best fit Lines
for (vector<Point> contour : contours){
    //Filter out contours that are too small
    if ((contourlength > 70.0) && (contours[idx].size() > 5)){
        Vec4f bestfitLine;
        fitLine(contour, bestfitLine,CV_DIST_L2,0,0.01,0.01);
        arrayofbestfits.push_back(bestfitLine);
    }
}
float SlopeTolerance = 0.05;
for (Vec4f firstIterationLine : arrayofbestfits){
    float firstIterationSlope = firstIterationLine[1]/firstIterationLine[0];
    for (Vec4f secondIterationLine : arrayofbestfits){
        //Filter out Lines too close in proxmity
        double length = cv::norm(Mat(Point(firstIterationLine[2],firstIterationLine[3])),
            Mat(Point(secondIterationLine[2],secondIterationLine[3])));
        if (length < 30){
            continue;
        }
        //Find slope between two points
        float commonSlope = (firstIterationLine[3]-secondIterationLine[3])
            /(firstIterationLine[2]-secondIterationLine[2]);
        //Find absolute value of differences (makes comparison simpler)
        float commonSlopediff = abs(firstIterationSlope - secondIterationSlope);
        float secondtocommonSlopediff = abs(secondIterationSlope - commonSlope);
        float commontofirstSlopediff = abs(commonSlope - firstIterationSlope);
        //If within tolerances draw the line bridging the two best fit lines together
        if ((commonSlopediff < SlopeTolerance) && (secondtocommonSlopediff < SlopeTolerance) && (commontofirstSlopediff < SlopeTolerance)){
            Line(frame,Point(firstIterationLine[2],firstIterationLine[3]),
                Point(secondIterationLine[2],secondIterationLine[3]),color,2);
        }
    }
}