diff --git a/modules/shape/include/opencv2/shape/shape_distance.hpp b/modules/shape/include/opencv2/shape/shape_distance.hpp
index 725b56ac9..94e20bc33 100644
--- a/modules/shape/include/opencv2/shape/shape_distance.hpp
+++ b/modules/shape/include/opencv2/shape/shape_distance.hpp
@@ -53,7 +53,7 @@ namespace cv
 //! @addtogroup shape
 //! @{
 
-/** @example samples/cpp/shape_example.cpp
+/** @example modules/shape/samples/shape_example.cpp
 An example using shape distance algorithm
 */
 /** @brief Abstract base class for shape distance algorithms.
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diff --git a/modules/shape/samples/data/shape_sample/9.png b/modules/shape/samples/data/shape_sample/9.png
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diff --git a/modules/shape/samples/shape_example.cpp b/modules/shape/samples/shape_example.cpp
new file mode 100644
index 000000000..514e4dc01
--- /dev/null
+++ b/modules/shape/samples/shape_example.cpp
@@ -0,0 +1,121 @@
+/*
+ * shape_context.cpp -- Shape context demo for shape matching
+ */
+
+#include "opencv2/shape.hpp"
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/highgui.hpp"
+#include "opencv2/imgproc.hpp"
+#include <opencv2/core/utility.hpp>
+#include <iostream>
+#include <string>
+
+using namespace std;
+using namespace cv;
+
+static void help()
+{
+    printf("\n"
+            "This program demonstrates a method for shape comparison based on Shape Context\n"
+            "You should run the program providing a number between 1 and 20 for selecting an image in the folder ../data/shape_sample.\n"
+            "Call\n"
+            "./shape_example [number between 1 and 20, 1 default]\n\n");
+}
+
+static vector<Point> simpleContour( const Mat& currentQuery, int n=300 )
+{
+    vector<vector<Point> > _contoursQuery;
+    vector <Point> contoursQuery;
+    findContours(currentQuery, _contoursQuery, RETR_LIST, CHAIN_APPROX_NONE);
+    for (size_t border=0; border<_contoursQuery.size(); border++)
+    {
+        for (size_t p=0; p<_contoursQuery[border].size(); p++)
+        {
+            contoursQuery.push_back( _contoursQuery[border][p] );
+        }
+    }
+
+    // In case actual number of points is less than n
+    int dummy=0;
+    for (int add=(int)contoursQuery.size()-1; add<n; add++)
+    {
+        contoursQuery.push_back(contoursQuery[dummy++]); //adding dummy values
+    }
+
+    // Uniformly sampling
+    cv::randShuffle(contoursQuery);
+    vector<Point> cont;
+    for (int i=0; i<n; i++)
+    {
+        cont.push_back(contoursQuery[i]);
+    }
+    return cont;
+}
+
+int main(int argc, char** argv)
+{
+    string path = "data/shape_sample/";
+    cv::CommandLineParser parser(argc, argv, "{help h||}{@input|1|}");
+    if (parser.has("help"))
+    {
+        help();
+        return 0;
+    }
+    int indexQuery = parser.get<int>("@input");
+    if (!parser.check())
+    {
+        parser.printErrors();
+        help();
+        return 1;
+    }
+    if (indexQuery < 1 || indexQuery > 20)
+    {
+        help();
+        return 1;
+    }
+    cv::Ptr <cv::ShapeContextDistanceExtractor> mysc = cv::createShapeContextDistanceExtractor();
+
+    Size sz2Sh(300,300);
+    stringstream queryName;
+    queryName<<path<<indexQuery<<".png";
+    Mat query=imread(queryName.str(), IMREAD_GRAYSCALE);
+    Mat queryToShow;
+    resize(query, queryToShow, sz2Sh, 0, 0, INTER_LINEAR_EXACT);
+    imshow("QUERY", queryToShow);
+    moveWindow("TEST", 0,0);
+    vector<Point> contQuery = simpleContour(query);
+    int bestMatch = 0;
+    float bestDis=FLT_MAX;
+    for ( int ii=1; ii<=20; ii++ )
+    {
+        if (ii==indexQuery) continue;
+        waitKey(30);
+        stringstream iiname;
+        iiname<<path<<ii<<".png";
+        cout<<"name: "<<iiname.str()<<endl;
+        Mat iiIm=imread(iiname.str(), 0);
+        Mat iiToShow;
+        resize(iiIm, iiToShow, sz2Sh, 0, 0, INTER_LINEAR_EXACT);
+        imshow("TEST", iiToShow);
+        moveWindow("TEST", sz2Sh.width+50,0);
+        vector<Point> contii = simpleContour(iiIm);
+        float dis = mysc->computeDistance( contQuery, contii );
+        if ( dis<bestDis )
+        {
+            bestMatch = ii;
+            bestDis = dis;
+        }
+        std::cout<<" distance between "<<queryName.str()<<" and "<<iiname.str()<<" is: "<<dis<<std::endl;
+    }
+    destroyWindow("TEST");
+    stringstream bestname;
+    bestname<<path<<bestMatch<<".png";
+    Mat iiIm=imread(bestname.str(), 0);
+    Mat bestToShow;
+    resize(iiIm, bestToShow, sz2Sh, 0, 0, INTER_LINEAR_EXACT);
+    imshow("BEST MATCH", bestToShow);
+    moveWindow("BEST MATCH", sz2Sh.width+50,0);
+    waitKey();
+
+    return 0;
+}
diff --git a/modules/shape/test_python/test_shape.py b/modules/shape/test_python/test_shape.py
new file mode 100644
index 000000000..1c9f07b7d
--- /dev/null
+++ b/modules/shape/test_python/test_shape.py
@@ -0,0 +1,26 @@
+#!/usr/bin/env python
+import cv2 as cv
+
+from tests_common import NewOpenCVTests
+
+class shape_test(NewOpenCVTests):
+
+    def test_computeDistance(self):
+
+        a = self.get_sample('samples/data/shape_sample/1.png', cv.IMREAD_GRAYSCALE)
+        b = self.get_sample('samples/data/shape_sample/2.png', cv.IMREAD_GRAYSCALE)
+
+        ca, _ = cv.findContours(a, cv.RETR_CCOMP, cv.CHAIN_APPROX_TC89_KCOS)
+        cb, _ = cv.findContours(b, cv.RETR_CCOMP, cv.CHAIN_APPROX_TC89_KCOS)
+
+        hd = cv.createHausdorffDistanceExtractor()
+        sd = cv.createShapeContextDistanceExtractor()
+
+        d1 = hd.computeDistance(ca[0], cb[0])
+        d2 = sd.computeDistance(ca[0], cb[0])
+
+        self.assertAlmostEqual(d1, 26.4196891785, 3, "HausdorffDistanceExtractor")
+        self.assertAlmostEqual(d2, 0.25804194808, 3, "ShapeContextDistanceExtractor")
+
+if __name__ == '__main__':
+    NewOpenCVTests.bootstrap()