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Morphological Skeletonization can be considered as a controlled erosion process. This involves shrinking the image until the area of interest is 1 pixel wide. This can allow quick and accurate image processing on an otherwise large and memory intensive operation. A great example of using skeletonization on an image is processing fingerprints.
In binary morphology, an image is viewed as a subset of a Euclidean space or the integer grid , for some dimension d.Let us denote this space or grid by E.. A structuring element is a simple, pre-defined shape, represented as a binary image, used to probe another binary image, in morphological operations such as erosion, dilation, opening, and closing.
In most cases in image processing thickening is performed by thinning the background [1] (,) = () where ∪ {\displaystyle \cup } denotes the set-theoretical difference and ⊙ {\displaystyle \odot } denotes the hit-or-miss transform , and B i {\displaystyle B_{i}} is the structural element and X {\displaystyle X} is the image being operated on.
In binary morphology, an image is viewed as a subset of a Euclidean space or the integer grid, for some dimension d.. The basic idea in binary morphology is to probe an image with a simple, pre-defined shape, drawing conclusions on how this shape fits or misses the shapes in the image.
Together with closing, the opening serves in computer vision and image processing as a basic workhorse of morphological noise removal. Opening removes small objects from the foreground (usually taken as the bright pixels) of an image, placing them in the background, while closing removes small holes in the foreground, changing small islands of ...
In mathematical morphology, a structuring element is a shape, used to probe or interact with a given image, with the purpose of drawing conclusions on how this shape fits or misses the shapes in the image. It is typically used in morphological operations, such as dilation, erosion, opening, and closing, as well as the hit-or-miss transform.
Example of dilation on a grayscale image using a 5x5 flat structuring element. The top figure demonstrates the application of the structuring element window to the individual pixels of the original image. The bottom figure shows the resulting dilated image. It is common to use flat structuring elements in morphological applications.
In mathematical morphology and digital image processing, a top-hat transform is an operation that extracts small elements and details from given images.There exist two types of top-hat transform: the white top-hat transform is defined as the difference between the input image and its opening by some structuring element, while the black top-hat transform is defined dually as the difference ...
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