erosiondilation

Erosion and dilation are two fundamental morphological operations used in image processing and computer vision. They are often applied in tandem or as part of more complex algorithms.

Erosion is an operation that shrinks or thins the boundaries of foreground objects in an image. It works by moving a structuring element (a small kernel or shape) across the image. For each position of the structuring element, the eroded pixel takes on the minimum value within the region covered by the element. This process effectively removes small noise speckles and disconnects objects that are close together.

Dilation, conversely, expands or thickens the boundaries of foreground objects. Similar to erosion, it uses a structuring element. For each position of the structuring element, the dilated pixel takes on the maximum value within the region covered by the element. Dilation can be used to fill in small holes within objects, connect nearby objects, or enlarge features.

These operations are often paired. Applying erosion followed by dilation is known as opening. Opening tends to remove small objects while preserving the shape and size of larger objects. Applying dilation followed by erosion is known as closing. Closing tends to smooth object contours, fill holes, and connect objects that are close but not touching. The choice of structuring element, its size, and shape significantly influence the outcome of both erosion and dilation.