diff --git a/modules/imgproc/include/opencv2/imgproc.hpp b/modules/imgproc/include/opencv2/imgproc.hpp
index ab46838160..1d94e748d5 100644
--- a/modules/imgproc/include/opencv2/imgproc.hpp
+++ b/modules/imgproc/include/opencv2/imgproc.hpp
@@ -386,7 +386,9 @@ enum GrabCutModes {
     automatically initialized with GC_BGD .*/
     GC_INIT_WITH_MASK  = 1,
     /** The value means that the algorithm should just resume. */
-    GC_EVAL            = 2
+    GC_EVAL            = 2,
+    /** The value means that the algorithm should just run the grabCut algorithm (a single iteration) with the fixed model */
+    GC_EVAL_FREEZE_MODEL = 3
 };
 
 //! distanceTransform algorithm flags
diff --git a/modules/imgproc/src/grabcut.cpp b/modules/imgproc/src/grabcut.cpp
index 615b52ea7c..6edce405cb 100644
--- a/modules/imgproc/src/grabcut.cpp
+++ b/modules/imgproc/src/grabcut.cpp
@@ -557,7 +557,10 @@ void cv::grabCut( InputArray _img, InputOutputArray _mask, Rect rect,
     if( iterCount <= 0)
         return;
 
-    if( mode == GC_EVAL )
+    if( mode == GC_EVAL_FREEZE_MODEL )
+        iterCount = 1;
+
+    if( mode == GC_EVAL || mode == GC_EVAL_FREEZE_MODEL )
         checkMask( img, mask );
 
     const double gamma = 50;
@@ -571,7 +574,8 @@ void cv::grabCut( InputArray _img, InputOutputArray _mask, Rect rect,
     {
         GCGraph<double> graph;
         assignGMMsComponents( img, mask, bgdGMM, fgdGMM, compIdxs );
-        learnGMMs( img, mask, compIdxs, bgdGMM, fgdGMM );
+        if( mode != GC_EVAL_FREEZE_MODEL )
+            learnGMMs( img, mask, compIdxs, bgdGMM, fgdGMM );
         constructGCGraph(img, mask, bgdGMM, fgdGMM, lambda, leftW, upleftW, upW, uprightW, graph );
         estimateSegmentation( graph, mask );
     }
diff --git a/modules/imgproc/test/test_grabcut.cpp b/modules/imgproc/test/test_grabcut.cpp
index 5b711b3edb..eae8b3e482 100644
--- a/modules/imgproc/test/test_grabcut.cpp
+++ b/modules/imgproc/test/test_grabcut.cpp
@@ -92,7 +92,9 @@ void CV_GrabcutTest::run( int /* start_from */)
     mask = Scalar(0);
     Mat bgdModel, fgdModel;
     grabCut( img, mask, rect, bgdModel, fgdModel, 0, GC_INIT_WITH_RECT );
-    grabCut( img, mask, rect, bgdModel, fgdModel, 2, GC_EVAL );
+    bgdModel.copyTo(exp_bgdModel);
+    fgdModel.copyTo(exp_fgdModel);
+    grabCut( img, mask, rect, bgdModel, fgdModel, 2, GC_EVAL_FREEZE_MODEL );
 
     // Multiply images by 255 for more visuality of test data.
     if( mask_prob.empty() )
@@ -105,12 +107,20 @@ void CV_GrabcutTest::run( int /* start_from */)
         exp_mask1 = (mask & 1) * 255;
         imwrite(string(ts->get_data_path()) + "grabcut/exp_mask1.png", exp_mask1);
     }
-
     if (!verify((mask & 1) * 255, exp_mask1))
     {
         ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
         return;
     }
+    // The model should not be changed after calling with GC_EVAL_FREEZE_MODEL
+    double sumBgdModel = cv::sum(cv::abs(bgdModel) - cv::abs(exp_bgdModel))[0];
+    double sumFgdModel = cv::sum(cv::abs(fgdModel) - cv::abs(exp_fgdModel))[0];
+    if (sumBgdModel >= 0.1 || sumFgdModel >= 0.1)
+    {
+        ts->printf(cvtest::TS::LOG, "sumBgdModel = %f, sumFgdModel = %f\n", sumBgdModel, sumFgdModel);
+        ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
+        return;
+    }
 
     mask = mask_prob;
     bgdModel.release();
@@ -124,7 +134,6 @@ void CV_GrabcutTest::run( int /* start_from */)
         exp_mask2 = (mask & 1) * 255;
         imwrite(string(ts->get_data_path()) + "grabcut/exp_mask2.png", exp_mask2);
     }
-
     if (!verify((mask & 1) * 255, exp_mask2))
     {
         ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);