Let I an image (grayscale or binary image) and let H a mask (structuring element) where H(i,j)∈R, for (i,j)∈Z^2
(I⊕H)(u,v)=max{I(u+i,v+j)+H(i,j)} for ((i,j)∈H)
Properties:
Brighter (dark features are reduced, bright features are thickened, background is brighter)
(I⊖H)(u,v)=min{I(u+i,v+j)-H(i,j)} for ((i,j)∈H)
Properties:
Darker (bright features are reduced, dark features are thickened, background is darker)
I∘H=(I⊖H)⊕H
Properties:
Remove point or noise.
I⋅H=(I⊕H)⊖H
Properties:
Remove gaps.
(I⊕H)-(I⊖H)
The follow operations, extract small elements and details from given images. These operations are used for various image processing tasks, such as feature extraction, background equalization, image enhancement, and others.
I-(I∘H)
Properties:
This operation is used for light objects on a dark background.
(I⋅H)-I
Properties:
This operation is used for dark objects on a light background.
Source:
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