diff --git a/modules/imgproc/include/opencv2/imgproc.hpp b/modules/imgproc/include/opencv2/imgproc.hpp
index 9e25825412..7d51c34dcb 100644
--- a/modules/imgproc/include/opencv2/imgproc.hpp
+++ b/modules/imgproc/include/opencv2/imgproc.hpp
@@ -3732,21 +3732,17 @@ CV_EXPORTS_W int connectedComponentsWithStats(InputArray image, OutputArray labe
 /** @brief Finds contours in a binary image.
 
 The function retrieves contours from the binary image using the algorithm @cite Suzuki85 . The contours
-are a useful tool for shape analysis and object detection and recognition. See squares.c in the
+are a useful tool for shape analysis and object detection and recognition. See squares.cpp in the
 OpenCV sample directory.
 
-@note Source image is modified by this function. Also, the function does not take into account
-1-pixel border of the image (it's filled with 0's and used for neighbor analysis in the algorithm),
-therefore the contours touching the image border will be clipped.
-
 @param image Source, an 8-bit single-channel image. Non-zero pixels are treated as 1's. Zero
-pixels remain 0's, so the image is treated as binary . You can use compare , inRange , threshold ,
-adaptiveThreshold , Canny , and others to create a binary image out of a grayscale or color one.
-The function modifies the image while extracting the contours. If mode equals to RETR_CCOMP
-or RETR_FLOODFILL, the input can also be a 32-bit integer image of labels (CV_32SC1).
-@param contours Detected contours. Each contour is stored as a vector of points.
-@param hierarchy Optional output vector, containing information about the image topology. It has
-as many elements as the number of contours. For each i-th contour contours[i] , the elements
+pixels remain 0's, so the image is treated as binary . You can use cv::compare, cv::inRange, cv::threshold ,
+cv::adaptiveThreshold, cv::Canny, and others to create a binary image out of a grayscale or color one.
+If mode equals to cv::RETR_CCOMP or cv::RETR_FLOODFILL, the input can also be a 32-bit integer image of labels (CV_32SC1).
+@param contours Detected contours. Each contour is stored as a vector of points (e.g.
+std::vector<std::vector<cv::Point> >).
+@param hierarchy Optional output vector (e.g. std::vector<cv::Vec4i>), containing information about the image topology. It has
+as many elements as the number of contours. For each i-th contour contours[i], the elements
 hierarchy[i][0] , hiearchy[i][1] , hiearchy[i][2] , and hiearchy[i][3] are set to 0-based indices
 in contours of the next and previous contours at the same hierarchical level, the first child
 contour and the parent contour, respectively. If for the contour i there are no next, previous,
diff --git a/modules/imgproc/test/test_contours.cpp b/modules/imgproc/test/test_contours.cpp
index d8d51f2fe1..851ec2c340 100644
--- a/modules/imgproc/test/test_contours.cpp
+++ b/modules/imgproc/test/test_contours.cpp
@@ -483,10 +483,26 @@ TEST(Imgproc_FindContours, hilbert)
     img.setTo(Scalar::all(0));
 
     drawContours(img, contours, 0, Scalar::all(255), 1);
-    //imshow("hilbert", img);
-    //waitKey();
+
     ASSERT_EQ(1, (int)contours.size());
     ASSERT_EQ(9832, (int)contours[0].size());
 }
 
+TEST(Imgproc_FindContours, border)
+{
+    Mat img;
+    copyMakeBorder(Mat::zeros(8, 10, CV_8U), img, 1, 1, 1, 1, BORDER_CONSTANT, Scalar(1));
+
+    std::vector<std::vector<cv::Point> > contours;
+    findContours(img, contours, RETR_LIST, CHAIN_APPROX_NONE);
+
+    Mat img_draw_contours = Mat::zeros(img.size(), CV_8U);
+    for (size_t cpt = 0; cpt < contours.size(); cpt++)
+    {
+      drawContours(img_draw_contours, contours, static_cast<int>(cpt), cv::Scalar(255));
+    }
+
+    ASSERT_TRUE(norm(img - img_draw_contours, NORM_INF) == 0.0);
+}
+
 /* End of file. */