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Merge pull request #9382 from StevenPuttemans:fix_9121
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@ -13,9 +13,9 @@ Theory
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@note The explanation below belongs to the book **Learning OpenCV** by Bradski and Kaehler.
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### Convolution
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### Correlation
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In a very general sense, convolution is an operation between every part of an image and an operator
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In a very general sense, correlation is an operation between every part of an image and an operator
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(kernel).
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### What is a kernel?
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@ -25,10 +25,10 @@ that array, which is typically located at the center.
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![](images/filter_2d_tutorial_kernel_theory.png)
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### How does convolution with a kernel work?
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### How does correlation with a kernel work?
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Assume you want to know the resulting value of a particular location in the image. The value of the
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convolution is calculated in the following way:
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correlation is calculated in the following way:
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-# Place the kernel anchor on top of a determined pixel, with the rest of the kernel overlaying the
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corresponding local pixels in the image.
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@ -91,7 +91,7 @@ Explanation
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-# *kernel*: The kernel to be scanned through the image
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-# *anchor*: The position of the anchor relative to its kernel. The location *Point(-1, -1)*
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indicates the center by default.
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-# *delta*: A value to be added to each pixel during the convolution. By default it is \f$0\f$
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-# *delta*: A value to be added to each pixel during the correlation. By default it is \f$0\f$
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-# *BORDER_DEFAULT*: We let this value by default (more details in the following tutorial)
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-# Our program will effectuate a *while* loop, each 500 ms the kernel size of our filter will be
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