如何繪制每個分割對象的輪廓

Question

我應用分水嶺分割來檢測觸摸對象，這樣做可以正常工作。 現在，我想繪制每個對象的輪廓，這樣我就可以得到它們的長度、面積、力矩等。但是分割結果中的對象仍然是觸摸的。 所以，我沒有畫出每一個的輪廓。 如何繪制每個對象的輪廓？

#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <iostream>

using namespace std;
using namespace cv;

int main()
{
    Mat src = imread("source.png");

    // Create binary image from source image
    Mat srcGray;
    cvtColor(src, srcGray, CV_BGR2GRAY);

    Mat srcThresh;
    threshold(srcGray, srcThresh, 0, 255, CV_THRESH_BINARY | CV_THRESH_OTSU);

    // Perform the distance transform algorithm
    Mat dist;
    distanceTransform(srcThresh, dist, CV_DIST_L2, 3);

    // Normalize the distance image for range = {0.0, 1.0}
    normalize(dist, dist, 0, 1., NORM_MINMAX);

    // Threshold to obtain the peaks 
    threshold(dist, dist, 0.1, 3.5, CV_THRESH_BINARY);

    // Create the CV_8U version of the distance image
    Mat dist_8u;
    dist.convertTo(dist_8u, CV_8U);

    // Find total markers
    std::vector<std::vector<Point> > contours;
    findContours(dist_8u, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
    int ncomp = contours.size();

    // Create the marker image for the watershed algorithm
    Mat markers = Mat::zeros(dist.size(), CV_32SC1);

    // Draw the foreground markers
    for (int i = 0; i < ncomp; i++)
        drawContours(markers, contours, i, Scalar::all(i + 1), -1);

    // Draw the background marker
    circle(markers, Point(5, 5), 3, CV_RGB(255, 255, 255), -1);

    // Perform the watershed algorithm
    watershed(src, markers);

    Mat wgResult = (markers.clone()) * 10000;

    imshow("Watershed", wgResult);

    waitKey(0);
    return 0;
}

源圖像：

分水嶺結果：

Answer 1

根據種子， watershed返回的markers矩陣包含分割區域的索引。 因此每個組件將具有相同的種子值。 然后，您可以為每個種子創建一個二進制矩陣，例如：

Mat1b mask = (markers == seed);

一旦有了每個組件的二進制掩碼，您就可以輕松計算其面積、矩等...

代碼：

#include <opencv2/opencv.hpp>
#include <iostream>
using namespace std;
using namespace cv;

int main()
{
    Mat src = imread("D:\\SO\\img\\postit.png");

    // Create binary image from source image
    Mat srcGray;
    cvtColor(src, srcGray, CV_BGR2GRAY);

    Mat srcThresh;
    threshold(srcGray, srcThresh, 0, 255, CV_THRESH_BINARY | CV_THRESH_OTSU);

    // Perform the distance transform algorithm
    Mat dist;
    distanceTransform(srcThresh, dist, CV_DIST_L2, 3);

    // Normalize the distance image for range = {0.0, 1.0}
    normalize(dist, dist, 0, 1., NORM_MINMAX);

    // Threshold to obtain the peaks 
    threshold(dist, dist, 0.1, 3.5, CV_THRESH_BINARY);

    // Create the CV_8U version of the distance image
    Mat dist_8u;
    dist.convertTo(dist_8u, CV_8U);

    // Find total markers
    std::vector<std::vector<Point> > contours;
    findContours(dist_8u, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
    int ncomp = contours.size();

    // Create the marker image for the watershed algorithm
    Mat markers = Mat::zeros(dist.size(), CV_32SC1);

    // Draw the foreground markers
    for (int i = 0; i < ncomp; i++)
        drawContours(markers, contours, i, Scalar::all(i + 1), -1);

    // Draw the background marker
    circle(markers, Point(5, 5), 3, CV_RGB(255, 255, 255), -1);

    // Perform the watershed algorithm
    watershed(src, markers);

    for (int seed = 1; seed <= ncomp; ++seed)
    {
        Mat1b mask = (markers == seed);

        // Now you have the mask, you can compute your statistics

        imshow("Mask", mask);
        waitKey();
    }

    return 0;
}

Answer 2

有很多方法可以做到這一點。 根據顯示的當前圖像，您可以簡單地進行腐蝕和膨脹操作以將它們分開。 但是，如果經過區域較大，這將不起作用。

您需要關閉操作： http : //docs.opencv.org/2.4/doc/tutorials/imgproc/opening_closure_hats/opening_closed_hats.html

1. 閾值它。
2. 應用關閉操作。
3. 獲取輪廓