diff --git a/doc/py_tutorials/py_video/py_meanshift/py_meanshift.rst b/doc/py_tutorials/py_video/py_meanshift/py_meanshift.rst
index a111311af3..87ece69350 100644
--- a/doc/py_tutorials/py_video/py_meanshift/py_meanshift.rst
+++ b/doc/py_tutorials/py_video/py_meanshift/py_meanshift.rst
@@ -52,7 +52,7 @@ To use meanshift in OpenCV, first we need to setup the target, find its histogra
 
     # set up the ROI for tracking
     roi = frame[r:r+h, c:c+w]
-    hsv_roi =  cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+    hsv_roi =  cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
     mask = cv2.inRange(hsv_roi, np.array((0., 60.,32.)), np.array((180.,255.,255.)))
     roi_hist = cv2.calcHist([hsv_roi],[0],mask,[180],[0,180])
     cv2.normalize(roi_hist,roi_hist,0,255,cv2.NORM_MINMAX)
@@ -127,7 +127,7 @@ It is almost same as meanshift, but it returns a rotated rectangle (that is our
 
     # set up the ROI for tracking
     roi = frame[r:r+h, c:c+w]
-    hsv_roi =  cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+    hsv_roi =  cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
     mask = cv2.inRange(hsv_roi, np.array((0., 60.,32.)), np.array((180.,255.,255.)))
     roi_hist = cv2.calcHist([hsv_roi],[0],mask,[180],[0,180])
     cv2.normalize(roi_hist,roi_hist,0,255,cv2.NORM_MINMAX)