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 中定义为向量（向量（点））。我想检查一个轮廓是否存在于另一个轮廓中。我还想知道，每个 OUTERCONT 中存在多少个轮廓。 我目前正在围绕每个轮廓绘制一个 minEnclosureRect 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，它总是将计数返回为 120 左右的某个数字，这是不对的。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 个不同函数返回的两组独立轮廓。

我知道 PointPloygon 测试是一种选择，但您能建议更多的方法吗？

Answer 1

这是我来自 cmets 的想法：

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

    cv::Mat input_red = cv::imread("C:/StackOverflow/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:/StackOverflow/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:/StackOverflow/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：

计算轮廓掩码并进行比较。

结果将按轮廓显示。黑色轮廓是参考，绿色是完全在参考内的轮廓，紫色是相交轮廓。

我正在使用这张图片来绘制结果：

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，没有检测到孤独的黄色轮廓与任何红色轮廓相交或包含在任何红色轮廓中。