Connected-component labeling (alternatively connected-component analysis, blob extraction, region labeling, blob discovery, or region extraction) is an algorithmic application of graph theory, where subsets of connected components are uniquely labeled based on a given heuristic. Connected-component labeling is not to be confused with segmentation.
Connected-component labeling is used in computer vision to detect connected regions in binary digital images, although color images and data with higher dimensionality can also be processed. When integrated into an image recognition system or human-computer interaction interface, connected component labeling can operate on a variety of information. Blob extraction is generally performed on the resulting binary image from a thresholding step. Blobs may be counted, filtered, and tracked.
Blob extraction is related to but distinct from blob detection.
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... A one pass version of the connected-component-labeling algorithm is given as follows ... Algorithm Connected-component matrix is initialized to size of image matrix ... Set the pixels indicated by Index to 1 in the connected-component matrix ...
Famous quotes containing the word labeling:
“Although adults have a role to play in teaching social skills to children, it is often best that they play it unobtrusively. In particular, adults must guard against embarrassing unskilled children by correcting them too publicly and against labeling children as shy in ways that may lead the children to see themselves in just that way.”
—Zick Rubin (20th century)