diff --git a/source/py_tutorials/py_feature2d/py_matcher/py_matcher.rst b/source/py_tutorials/py_feature2d/py_matcher/py_matcher.rst
index b81130b..5a5ed27 100644
--- a/source/py_tutorials/py_feature2d/py_matcher/py_matcher.rst
+++ b/source/py_tutorials/py_feature2d/py_matcher/py_matcher.rst
@@ -33,7 +33,7 @@ Brute-Force Matching with ORB Descriptors
 
 Here, we will see a simple example on how to match features between two images. In this case, I have a queryImage and a trainImage. We will try to find the queryImage in trainImage using feature matching. ( The images are ``/samples/c/box.png`` and ``/samples/c/box_in_scene.png``)
 
-We are using SIFT descriptors to match features. So let's start with loading images, finding descriptors etc.
+We are using ORB descriptors to match features. So let's start with loading images, finding descriptors etc.
 ::
 
     import numpy as np
@@ -43,10 +43,10 @@ We are using SIFT descriptors to match features. So let's start with loading ima
     img1 = cv2.imread('box.png',0)          # queryImage
     img2 = cv2.imread('box_in_scene.png',0) # trainImage
 
-    # Initiate SIFT detector
+    # Initiate ORB detector
     orb = cv2.ORB()
 
-    # find the keypoints and descriptors with SIFT
+    # find the keypoints and descriptors with ORB
     kp1, des1 = orb.detectAndCompute(img1,None)
     kp2, des2 = orb.detectAndCompute(img2,None)