OpenCV，如何使用点数组来平滑和采样轮廓？ [英] OpenCV, how to use arrays of points for smoothing and sampling contours?

问题描述

我有一个问题，让我围绕平滑和抽样轮廓在OpenCV（C ++ API）。
假设我有从 cv :: findContours 中检索的点序列（例如应用于此图像：

>

最终，我想要

1. 使用不同的内核来平滑点序列。






平滑后，我希望有一个结果：





>





我也考虑在 cv :: Mat 中绘制我的轮廓，过滤Mat（使用模糊或形态运算）和重新找到轮廓，但是慢和次优。所以，理想情况下，我可以使用排序的点序列。





我读了几个帖子，天真地认为，我可以简单地转换 std :: vector （ cv :: Point ）复制到 cv :: Mat 然后OpenCV的功能，像模糊/调整大小会为我做的工作，但他们没有。





这是我尝试：

  int main（int argc，char ** argv）{
 
 cv :: Mat conv，ori; 
 ori = cv :: imread（argv [1]）; 
 ori.copyTo（conv）; 
 cv :: cvtColor（ori，ori，CV_BGR2GRAY）; 
 
 std :: vector< std :: vector< cv :: Point> >轮廓; 
 std :: vector< cv :: Vec4i>层次; 
 
 cv :: findContours（ori，contour，hierarchy，CV_RETR_CCOMP，CV_CHAIN_APPROX_NONE）; 
 
 for（int k = 0; k <100; k + = 2）{
 cv :: Mat smoothCont; 
 
 smoothCont = cv :: Mat（contoururs [0]）; 
 std :: cout<< smoothCont.rows<<\t<< smoothCont.cols<< std :: endl; 
 / *尝试平滑：不修改数组* / 
 // cv :: GaussianBlur（smoothCont，smoothCont，cv :: Size（k + 1,1），k）; 
 / *尝试抽样：调整失败（func！= 0）in resize* / 
 // cv :: resize（smoothCont，smoothCont，cv :: Size（0,0），1， 1）; 
 std :: vector< std :: vector< cv :: Point> > v（1）; 
 smoothCont.copyTo（v [0]）; 
 cv :: drawContours（conv，v，0，cv :: Scalar（255,0,0），2，CV_AA）; 
 std :: cout<< k<< std :: endl; 
 cv :: imshow（conv，conv）; 
 cv :: waitKey（）; 
} 
 return 1; 
} 
  

任何人都可以解释怎么做？





此外，由于我可能使用更小的轮廓，我想知道这种方法如何处理边界效果（例如，当平滑时，由于轮廓是圆形的，因此序列的最后一个元素必须是用于计算第一个元素的新值...）





非常感谢您的建议，





修改：





我也尝试过 cv :: approxPolyDP（）正如你所看到的，它倾向于保存极值点（我要删除）：





Epsilon = 0








Epsilon = 6





>





Epsilon = 12








Epsilon = 24








编辑2：
正如Ben所建议的，看起来不支持 cv :: GaussianBlur（），但是 cv :: blur（）是。它看起来非常接近我的期望。以下是我使用它的结果：





k = 13








k = 53








k = 103





>





为了避开边框效果，我做了：

  cv :: copyMakeBorder smoothCont，smoothCont，（k-1）/ 2，（k-1）/ 2,0,0，cv :: BORDER_WRAP）; 
 cv :: blur（smoothCont，result，cv :: Size（1，k），cv :: Point（-1，-1））; 
 result.rowRange（cv :: Range（（k-1）/2,1+result.rows-（k-1）/ 2））。copyTo（v [0]）; 
  

我还在寻找解决方案来插值/抽样我的轮廓。

解决方案

您的高斯模糊不工作，因为您在列方向模糊，但只有一列。使用 GaussianBlur（）导致OpenCV中的功能未实现错误，当尝试将向量复制到 cv :: Mat （这可能是为什么你有这个奇怪的 resize（）在你的代码），但一切工作正常使用 cv :: blur ，无需 resize（）。尝试大小（0,41）例如。使用 cv :: BORDER_WRAP 似乎也不工作，但这里是另一个人的线程，发现了一个解决方法。





更多的事情：你说你的轮廓可能会小得多。这种方式平滑你的轮廓会收缩它。极端情况是 k = size_of_contour ，这产生一个点。所以不要选择你的k太大。




I have a problem to get my head around smoothing and sampling contours in OpenCV (C++ API). Lets say I have got sequence of points retrieved from cv::findContours (for instance applied on this this image:

Ultimately, I want

1. To smooth a sequence of points using different kernels.
2. To resize the sequence using different types of interpolations.

After smoothing, I hope to have a result like :

I also considered drawing my contour in a cv::Mat, filtering the Mat (using blur or morphological operations) and re-finding the contours, but is slow and suboptimal. So, ideally, I could do the job using exclusively the point sequence.

I read a few posts on it and naively thought that I could simply convert a std::vector(of cv::Point) to a cv::Mat and then OpenCV functions like blur/resize would do the job for me... but they did not.

Here is what I tried:

int main( int argc, char** argv ){

    cv::Mat conv,ori;
    ori=cv::imread(argv[1]);
    ori.copyTo(conv);
    cv::cvtColor(ori,ori,CV_BGR2GRAY);

    std::vector<std::vector<cv::Point> > contours;
    std::vector<cv::Vec4i > hierarchy;

    cv::findContours(ori, contours,hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_NONE);

    for(int k=0;k<100;k += 2){
        cv::Mat smoothCont;

        smoothCont = cv::Mat(contours[0]);
        std::cout<<smoothCont.rows<<"\t"<<smoothCont.cols<<std::endl;
        /* Try smoothing: no modification of the array*/
//        cv::GaussianBlur(smoothCont, smoothCont, cv::Size(k+1,1),k);
        /* Try sampling: "Assertion failed (func != 0) in resize"*/
//        cv::resize(smoothCont,smoothCont,cv::Size(0,0),1,1);
        std::vector<std::vector<cv::Point> > v(1);
        smoothCont.copyTo(v[0]);
        cv::drawContours(conv,v,0,cv::Scalar(255,0,0),2,CV_AA);
        std::cout<<k<<std::endl;
        cv::imshow("conv", conv);
        cv::waitKey();
    }
    return 1;
}

Could anyone explain how to do this ?

In addition, since I am likely to work with much smaller contours, I was wondering how this approach would deal with border effect (e.g. when smoothing, since contours are circular, the last elements of a sequence must be used to calculate the new value of the first elements...)

Thank you very much for your advices,

Edit:

I also tried cv::approxPolyDP() but, as you can see, it tends to preserve extremal points (which I want to remove):

Epsilon=0

Epsilon=6

Epsilon=12

Epsilon=24

Edit 2: As suggested by Ben, it seems that cv::GaussianBlur() is not supported but cv::blur() is. It looks very much closer to my expectation. Here are my results using it:

k=13

k=53

k=103

To get around the border effect, I did:

    cv::copyMakeBorder(smoothCont,smoothCont, (k-1)/2,(k-1)/2 ,0, 0, cv::BORDER_WRAP);
    cv::blur(smoothCont, result, cv::Size(1,k),cv::Point(-1,-1));
    result.rowRange(cv::Range((k-1)/2,1+result.rows-(k-1)/2)).copyTo(v[0]);

I am still looking for solutions to interpolate/sample my contour.

解决方案

Your Gaussian blurring doesn't work because you're blurring in column direction, but there is only one column. Using GaussianBlur() leads to a "feature not implemented" error in OpenCV when trying to copy the vector back to a cv::Mat (that's probably why you have this strange resize() in your code), but everything works fine using cv::blur(), no need to resize(). Try Size(0,41) for example. Using cv::BORDER_WRAP for the border issue doesn't seem to work either, but here is another thread of someone who found a workaround for that.

Oh... one more thing: you said that your contours are likely to be much smaller. Smoothing your contour that way will shrink it. The extreme case is k = size_of_contour, which results in a single point. So don't choose your k too big.

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