Merge pull request #9382 from StevenPuttemans:fix_9121

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Alexander Alekhin 2017-08-16 13:56:33 +00:00 committed by GitHub
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@ -13,9 +13,9 @@ Theory
@note The explanation below belongs to the book **Learning OpenCV** by Bradski and Kaehler.
### Convolution
### Correlation
In a very general sense, convolution is an operation between every part of an image and an operator
In a very general sense, correlation is an operation between every part of an image and an operator
(kernel).
### What is a kernel?
@ -25,10 +25,10 @@ that array, which is typically located at the center.
![](images/filter_2d_tutorial_kernel_theory.png)
### How does convolution with a kernel work?
### How does correlation with a kernel work?
Assume you want to know the resulting value of a particular location in the image. The value of the
convolution is calculated in the following way:
correlation is calculated in the following way:
-# Place the kernel anchor on top of a determined pixel, with the rest of the kernel overlaying the
corresponding local pixels in the image.
@ -91,7 +91,7 @@ Explanation
-# *kernel*: The kernel to be scanned through the image
-# *anchor*: The position of the anchor relative to its kernel. The location *Point(-1, -1)*
indicates the center by default.
-# *delta*: A value to be added to each pixel during the convolution. By default it is \f$0\f$
-# *delta*: A value to be added to each pixel during the correlation. By default it is \f$0\f$
-# *BORDER_DEFAULT*: We let this value by default (more details in the following tutorial)
-# Our program will effectuate a *while* loop, each 500 ms the kernel size of our filter will be