diff --git a/doc/py_tutorials/py_calib3d/py_calibration/py_calibration.markdown b/doc/py_tutorials/py_calib3d/py_calibration/py_calibration.markdown
index 66f578f33..3655400f3 100644
--- a/doc/py_tutorials/py_calib3d/py_calibration/py_calibration.markdown
+++ b/doc/py_tutorials/py_calib3d/py_calibration/py_calibration.markdown
@@ -22,17 +22,17 @@ red line. All the expected straight lines are bulged out. Visit [Distortion
 
 ![image](images/calib_radial.jpg)
 
-This distortion is solved as follows:
+This distortion is represented as follows:
 
-\f[x_{corrected} = x( 1 + k_1 r^2 + k_2 r^4 + k_3 r^6) \\
-y_{corrected} = y( 1 + k_1 r^2 + k_2 r^4 + k_3 r^6)\f]
+\f[x_{distorted} = x( 1 + k_1 r^2 + k_2 r^4 + k_3 r^6) \\
+y_{distorted} = y( 1 + k_1 r^2 + k_2 r^4 + k_3 r^6)\f]
 
 Similarly, another distortion is the tangential distortion which occurs because image taking lense
 is not aligned perfectly parallel to the imaging plane. So some areas in image may look nearer than
-expected. It is solved as below:
+expected. It is represented as below:
 
-\f[x_{corrected} = x + [ 2p_1xy + p_2(r^2+2x^2)] \\
-y_{corrected} = y + [ p_1(r^2+ 2y^2)+ 2p_2xy]\f]
+\f[x_{distorted} = x + [ 2p_1xy + p_2(r^2+2x^2)] \\
+y_{distorted} = y + [ p_1(r^2+ 2y^2)+ 2p_2xy]\f]
 
 In short, we need to find five parameters, known as distortion coefficients given by:
 
diff --git a/doc/tutorials/calib3d/camera_calibration/camera_calibration.markdown b/doc/tutorials/calib3d/camera_calibration/camera_calibration.markdown
index a7bd1f059..1a7b90687 100644
--- a/doc/tutorials/calib3d/camera_calibration/camera_calibration.markdown
+++ b/doc/tutorials/calib3d/camera_calibration/camera_calibration.markdown
@@ -14,18 +14,18 @@ Theory
 For the distortion OpenCV takes into account the radial and tangential factors. For the radial
 factor one uses the following formula:
 
-\f[x_{corrected} = x( 1 + k_1 r^2 + k_2 r^4 + k_3 r^6) \\
-y_{corrected} = y( 1 + k_1 r^2 + k_2 r^4 + k_3 r^6)\f]
+\f[x_{distorted} = x( 1 + k_1 r^2 + k_2 r^4 + k_3 r^6) \\
+y_{distorted} = y( 1 + k_1 r^2 + k_2 r^4 + k_3 r^6)\f]
 
-So for an old pixel point at \f$(x,y)\f$ coordinates in the input image, its position on the corrected
-output image will be \f$(x_{corrected} y_{corrected})\f$. The presence of the radial distortion
-manifests in form of the "barrel" or "fish-eye" effect.
+So for an undistorted pixel point at \f$(x,y)\f$ coordinates, its position on the distorted image
+will be \f$(x_{distorted} y_{distorted})\f$. The presence of the radial distortion manifests in form
+of the "barrel" or "fish-eye" effect.
 
 Tangential distortion occurs because the image taking lenses are not perfectly parallel to the
-imaging plane. It can be corrected via the formulas:
+imaging plane. It can be represented via the formulas:
 
-\f[x_{corrected} = x + [ 2p_1xy + p_2(r^2+2x^2)] \\
-y_{corrected} = y + [ p_1(r^2+ 2y^2)+ 2p_2xy]\f]
+\f[x_{distorted} = x + [ 2p_1xy + p_2(r^2+2x^2)] \\
+y_{distorted} = y + [ p_1(r^2+ 2y^2)+ 2p_2xy]\f]
 
 So we have five distortion parameters which in OpenCV are presented as one row matrix with 5
 columns: