Try to clarify the morphological operations in the tutorial to avoid possible confusions.

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catree 2016-10-09 23:45:04 +02:00
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6 changed files with 25 additions and 1 deletions

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@ -44,6 +44,14 @@ Morphological Operations
The background (bright) dilates around the black regions of the letter.
To better grasp the idea and avoid possible confusion, in this another example we have inverted the original
image such as the object in white is now the letter. We have performed two dilatations with a rectangular
structuring element of size `3x3`.
![Left image: original image inverted, right image: resulting dilatation](images/Morphology_1_Tutorial_Theory_Dilatation_2.png)
The dilatation makes the object in white bigger.
### Erosion
- This operation is the sister of dilation. What this does is to compute a local minimum over the
@ -56,6 +64,13 @@ The background (bright) dilates around the black regions of the letter.
![](images/Morphology_1_Tutorial_Theory_Erosion.png)
In the same manner, the corresponding image resulting of the erosion operation on the inverted original image (two erosions
with a rectangular structuring element of size `3x3`):
![Left image: original image inverted, right image: resulting erosion](images/Morphology_1_Tutorial_Theory_Erosion_2.png)
The erosion makes the object in white smaller.
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@ -24,7 +24,7 @@ In the previous tutorial we covered two basic Morphology operations:
- Dilation.
Based on these two we can effectuate more sophisticated transformations to our images. Here we
discuss briefly 05 operations offered by OpenCV:
discuss briefly 5 operations offered by OpenCV:
### Opening
@ -40,6 +40,11 @@ discuss briefly 05 operations offered by OpenCV:
![](images/Morphology_2_Tutorial_Theory_Opening.png)
For the sake of clarity, we have performed the opening operation (`7x7` rectangular structuring element)
on the same original image but inverted such as the object in white is now the letter.
![Left image: original image inverted, right image: resulting opening](images/Morphology_2_Tutorial_Theory_Opening_2.png)
### Closing
- It is obtained by the dilation of an image followed by an erosion.
@ -50,6 +55,10 @@ discuss briefly 05 operations offered by OpenCV:
![](images/Morphology_2_Tutorial_Theory_Closing.png)
On the inverted image, we have performed the closing operation (`7x7` rectangular structuring element):
![Left image: original image inverted, right image: resulting closing](images/Morphology_2_Tutorial_Theory_Closing_2.png)
### Morphological Gradient
- It is the difference between the dilation and the erosion of an image.