What is Morphological Image Processing?
Morphological image processing transforms shapes in binary or grayscale images using a structuring element. Core operations include erosion, dilation, opening, and closing.
How Morphological Image Processing works
Morphological processing evaluates image structure through a small probe called a structuring element. As that probe moves across the raster, set operations or local extrema expand, contract, connect, or separate foreground regions according to its geometry. Compositions such as opening and closing target small protrusions or gaps while preserving larger forms. These operations commonly refine segmentation masks before measurement, recognition, vectorization, or compositing.
Key facts
- 1On binary images, dilation expands foreground according to the structuring element and erosion contracts it. Reversing foreground convention reverses the visual interpretation.
- 2For grayscale morphology with a flat structuring element, dilation selects a local maximum and erosion a local minimum; non-flat elements additionally offset sample values.
- 3Opening is erosion followed by dilation, while closing reverses that order. With a fixed structuring element, repeating either completed operation does not keep changing the result.
When Morphological Image Processing matters
Use morphological operations to remove small artifacts, join gaps, isolate boundaries, or refine segmentation masks. The structuring element’s shape and size determine which features survive or disappear.