diff --git a/modules/js/src/embindgen.py b/modules/js/src/embindgen.py
index 64f009d8c2..ea5a939903 100644
--- a/modules/js/src/embindgen.py
+++ b/modules/js/src/embindgen.py
@@ -112,7 +112,7 @@ imgproc = {'': ['Canny', 'GaussianBlur', 'Laplacian', 'HoughLines', 'HoughLinesP
                 'goodFeaturesToTrack','grabCut','initUndistortRectifyMap', 'integral','integral2', 'isContourConvex', 'line', \
                 'matchShapes', 'matchTemplate','medianBlur', 'minAreaRect', 'minEnclosingCircle', 'moments', 'morphologyEx', \
                 'pointPolygonTest', 'putText','pyrDown','pyrUp','rectangle','remap', 'resize','sepFilter2D','threshold', \
-                'undistort','warpAffine','warpPerspective','watershed', \
+                'undistort','warpAffine','warpPerspective','warpPolar','watershed', \
                 'fillPoly', 'fillConvexPoly'],
            'CLAHE': ['apply', 'collectGarbage', 'getClipLimit', 'getTilesGridSize', 'setClipLimit', 'setTilesGridSize']}
 
@@ -143,7 +143,7 @@ features2d = {'Feature2D': ['detect', 'compute', 'detectAndCompute', 'descriptor
               'BFMatcher': ['isMaskSupported', 'create'],
               '': ['drawKeypoints', 'drawMatches', 'drawMatchesKnn']}
 
-calib3d = {'': ['findHomography', 'Rodrigues']}
+calib3d = {'': ['findHomography', 'estimateAffine2D', 'Rodrigues']}
 
 def makeWhiteList(module_list):
     wl = {}
diff --git a/modules/js/test/test_calib3d.js b/modules/js/test/test_calib3d.js
index d03c659dbe..b0001dbc67 100644
--- a/modules/js/test/test_calib3d.js
+++ b/modules/js/test/test_calib3d.js
@@ -65,3 +65,27 @@ QUnit.test('Rodrigues', function(assert) {
   assert.ok(1.01 > rvec1.data64F[0] > 0.9);
   // Answer should be around 1: 0.9999999999999999
 });
+
+QUnit.test('estimateAffine2D', function(assert) {
+   const inputs = cv.matFromArray(4, 1, cv.CV_32FC2, [
+    1, 1,
+    80, 0,
+    0, 80,
+    80, 80
+  ]);
+  const outputs = cv.matFromArray(4, 1, cv.CV_32FC2, [
+    21, 51,
+    70, 77,
+    40, 40,
+    10, 70
+  ]);
+  const M = cv.estimateAffine2D(inputs, outputs);
+  assert.ok(M instanceof cv.Mat);
+  assert.deepEqual(Array.from(M.data), [
+     23,  55,  97, 126,  87, 139, 227,  63,   0,   0,
+      0,   0,   0,   0, 232, 191,  71, 246,  12,  68,
+    165,  35,  53,  64,  99,  56,  27,  66,  14, 254,
+    212,  63, 103, 102, 102, 102, 102, 102, 182, 191,
+    195, 252, 174,  22,  55,  97,  73,  64
+  ]);
+});
diff --git a/modules/js/test/test_imgproc.js b/modules/js/test/test_imgproc.js
index 14977f5516..9ba5cd4e38 100644
--- a/modules/js/test/test_imgproc.js
+++ b/modules/js/test/test_imgproc.js
@@ -960,3 +960,20 @@ QUnit.test('test_filter', function(assert) {
         src.delete();
     }
 });
+
+QUnit.test('warpPolar', function(assert) {
+  const lines = new cv.Mat(255, 255, cv.CV_8U, new cv.Scalar(0));
+  for (let r = 0; r < lines.rows; r++) {
+    lines.row(r).setTo(new cv.Scalar(r));
+  }
+  cv.warpPolar(lines, lines, { width: 5, height: 5 }, new cv.Point(2, 2), 3,
+    cv.INTER_CUBIC | cv.WARP_FILL_OUTLIERS | cv.WARP_INVERSE_MAP);
+  assert.ok(lines instanceof cv.Mat);
+  assert.deepEqual(Array.from(lines.data), [
+    159, 172, 191, 210, 223,
+    146, 159, 191, 223, 236,
+    128, 128,   0,   0,   0,
+    109,  96,  64,  32,  19,
+     96,  83,  64,  45,  32
+  ]);
+});