搜索一个轮廓是否存在于另一个轮廓内

Question

我有两个轮廓向量 OUTERCONT 和 INNERCONT 在 openCV 中定义为 vector(vector(Points))。我想检查内部是否存在一个轮廓 another.I 还想知道每个 OUTERCONT 内部存在多少个轮廓。我目前正在每个轮廓周围绘制一个 minEnclosingRect 并检查以下内容：

for (int i = 0; i < outerrect.size(); i++)
{
    count = 0;
    for (int j = 0; j < innerrect.size(); j++)
    {
        bool is_inside = ((innerrect[j] & outerrect[i]) == innerrect[j]);
        if (is_inside == 1)
            count++;

    }
    if (count > 0)
    {
       //DO SOMETHING 
    }
    cout << count << endl;

这似乎不起作用，它总是 returns 计数为 120 左右的某个数字，这是不正确的。您能否建议任何更改以使其正常工作？

注意：我不能使用层次结构，因为这是从 2 个不同的函数返回的两组独立的轮廓。

我知道 PointPloygon 测试是一个选项，但你能建议更多的方法吗？

Answer 1

这是我从评论中得出的想法：

// stacked contours
int main(int argc, char* argv[])
{
    cv::Mat input = cv::imread("C:/Whosebug/Input/Contours_in_Contours.png");

    cv::Mat input_red = cv::imread("C:/Whosebug/Input/Contours_in_Contours_RED.png");

    cv::Mat reds;
    cv::inRange(input_red, cv::Scalar(0, 0, 200), cv::Scalar(50, 50, 255), reds);
    std::vector<std::vector<cv::Point> > contours1;
    cv::findContours(reds, contours1, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);

    cv::Mat input_yellow = cv::imread("C:/Whosebug/Input/Contours_in_Contours_YELLOW.png");

    cv::Mat yellows;
    cv::inRange(input, cv::Scalar(0, 200, 200), cv::Scalar(0, 255, 255), yellows);
    std::vector<std::vector<cv::Point> > contours2;
    cv::findContours(yellows, contours2, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);

    // now we have 2 sets of contours and want to find out whether contours of set2 are completely within a contour of contours1 without hierarchy information.

    std::vector<cv::Mat> masks1;
    std::vector<int> nMaskPixels1;
    // for each contour in contours1: create a contour mask:
    for (int i = 0; i < contours1.size(); ++i)
    {
        cv::Mat mask1 = cv::Mat::zeros(input.size(), CV_8UC1);
        cv::drawContours(mask1, contours1, i, cv::Scalar::all(255), -1); // draw filled
        int nPixel1 = cv::countNonZero(mask1);

        masks1.push_back(mask1);
        nMaskPixels1.push_back(nPixel1);
    }

    std::vector<cv::Mat> masks2;
    std::vector<int> nMaskPixels2;
    // for each contour in contours2: test whether it is completely within the reference contour:
    for (int j = 0; j < contours2.size(); ++j)
    {
        cv::Mat mask2 = cv::Mat::zeros(input.size(), CV_8UC1);
        cv::drawContours(mask2, contours2, j, cv::Scalar::all(255), -1); // draw filled
        int nPixel2 = cv::countNonZero(mask2);

        masks2.push_back(mask2);
        nMaskPixels2.push_back(nPixel2);
    }

    for (int i = 0; i < masks1.size(); ++i)
    {
        cv::Mat mask1 = masks1[i];

        // draw mask again for visualization:
        cv::Mat outIm = input.clone();
        cv::drawContours(outIm, contours1, i, cv::Scalar(0, 0, 0), 3);

        for (int j = 0; j < masks2.size(); ++j)
        {
            cv::Mat mask2 = masks2[j];

            cv::Mat overlap = mask1 & mask2;
            int nOverlapPixels = cv::countNonZero(overlap);
            if (nOverlapPixels == 0) continue; // no overlap at all. Test next contour.

            if (nOverlapPixels == nMaskPixels2[j] && nOverlapPixels < nMaskPixels1[i])
            {
                // second contour is completely within first contour
                cv::drawContours(outIm, contours2, j, cv::Scalar(0, 255, 0), 3);
            }
            else if (nOverlapPixels == nMaskPixels2[j] && nOverlapPixels == nMaskPixels1[i])
            {
                // both contours are identical
                std::cout << "WARNING: " << "contours " << i << " and " << j << " are identical" << std::endl;
            }
            else if (nOverlapPixels < nMaskPixels2[j] && nOverlapPixels == nMaskPixels1[i])
            {
                // first contour is completely within second contour
                std::cout << "WARNING: " << "contour " << i << " of the first set is inside of " << j << std::endl;
            }
            else if (nOverlapPixels < nMaskPixels2[j] && nOverlapPixels < nMaskPixels1[i])
            {
                // both contours intersect
                cv::drawContours(outIm, contours2, j, cv::Scalar(255, 0, 255), 3);
            }

        }

        cv::imshow("contours", outIm);
        cv::imwrite("C:/Whosebug/Output/contours.png", outIm);
        cv::waitKey(0);

    }



    cv::imshow("input", input);
    cv::waitKey(0);
    return 0;
}

此代码将从这 2 个图像创建两组轮廓：

计算轮廓蒙版并进行比较。

每个轮廓将显示结果。黑色轮廓是参考，绿色是完全在参考范围内的轮廓，紫色是交叉轮廓。

我正在使用此图像绘制结果：

得到这些结果：

轮廓1：

轮廓2：

轮廓3：

轮廓4：

轮廓5：

如您所见，未检测到孤立的黄色轮廓与任何这些红色轮廓相交或包含在其中。

搜索一个轮廓是否存在于另一个轮廓内

Search if a contour exists inside another contour

c++

opencv

image-processing

opencv-contour