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you need the edges of the cards to be preserved, therefore the smoothing that you are applying is not useful. Instead a sharpening algorithm should be applied. The following code works for the second image but not for the first. You need to find a sharpening kernel/solution that will help you preserve the edges.

#include <opencv2/opencv.hpp>
#include <iostream>

using namespace cv;
using namespace std;

int main()
{
    cv::Mat src = cv::imread("cards.jpg");
    if (!src.data)
        return -1;

    imshow("src", src);

    // Create binary image from source image
    cv::Mat bw;
    cv::cvtColor(src, bw, CV_BGR2GRAY);

    cv::threshold(bw, bw, 40, 255, CV_THRESH_BINARY | CV_THRESH_OTSU);
    imshow("bin", bw);

    // Fill holes
    cv::floodFill(bw,cv::Point2i(0,0),cv::Scalar(1));
    for(int i=0;i<bw.rows*bw.cols;i++)
    {
        if(bw.data[i]==0)
            bw.data[i]=255;
    }

    cv::threshold(bw, bw, 40, 255, CV_THRESH_BINARY | CV_THRESH_OTSU);

    imshow("filled", bw);

    cv::Mat dist;
    cv::distanceTransform(bw, dist, CV_DIST_L2, 3);
    cv::normalize(dist, dist, 0, 1., cv::NORM_MINMAX);
    imshow("Distance Transform Image", dist);

    cv::threshold(dist, dist, .5, 1., CV_THRESH_BINARY);

//    // Dilate a bit the dist image
//    Mat kernel1 = Mat::ones(7, 7, CV_8UC1);
//    dilate(dist, dist, kernel1);
//    erode(dist, dist, kernel1);
//    imshow("Peaks", dist);

    // Create the CV_8U version of the distance image
    // It is needed for cv::findContours()
    cv::Mat dist_8u;
    dist.convertTo(dist_8u, CV_8U);

    // Find total markers
    std::vector<std::vector<cv::Point> > contours;
    cv::findContours(dist_8u, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);

    // Total objects
    int ncomp = contours.size();

    cv::Mat markers = cv::Mat::zeros(dist.size(), CV_32SC1);
    for (int i = 0; i < ncomp; i++)
        cv::drawContours(markers, contours, i, cv::Scalar::all(i+1), -1);

    cv::circle(markers, cv::Point(5,5), 3, CV_RGB(255,255,255), -1);
    imshow("Markers", markers*10000);

    cv::watershed(src, markers);

    // Generate random colors
    std::vector<cv::Vec3b> colors;
    for (int i = 0; i < ncomp; i++)
    {
        int b = cv::theRNG().uniform(0, 255);
        int g = cv::theRNG().uniform(0, 255);
        int r = cv::theRNG().uniform(0, 255);

        colors.push_back(cv::Vec3b((uchar)b, (uchar)g, (uchar)r));
    }

    // Create the result image
    cv::Mat dst = cv::Mat::zeros(markers.size(), CV_8UC3);

    // Fill labeled objects with random colors
    for (int i = 0; i < markers.rows; i++)
    {
        for (int j = 0; j < markers.cols; j++)
        {
            int index = markers.at<int>(i,j);
            if (index > 0 && index <= ncomp)
                dst.at<cv::Vec3b>(i,j) = colors[index-1];
            else
                dst.at<cv::Vec3b>(i,j) = cv::Vec3b(0,0,0);
        }
    }

    cv::imshow("dst", dst);

    cv::waitKey(0);
    return 0;
}