Looking for the source code to this post? Jump Right To The Downloads Section OpenCV Connected Component Labeling and Analysis To learn how to perform connected component labeling and analysis with OpenCV, just keep reading. This is exactly what we’ll be doing here today.Ĭonnected component analysis is another tool to add to your OpenCV toolbelt! With connected component analysis, we can more easily segment and analyze these structures.Ī great example of connected component analysis is computing the connected components of a binary (i.e., thresholded) license plate image and filtering the blobs based on their properties (e.g., width, height, area, solidity, etc.). When using contour analysis, we are often restricted by the hierarchy of the outlines (i.e., one contour contained within another). We often use connected component analysis in the same situations that contours are used however, connected component labeling can often give us more granular filtering of the blobs in a binary image. Connected component labeling (also known as connected component analysis, blob extraction, or region labeling) is an algorithmic application of graph theory used to determine the connectivity of “blob”-like regions in a binary image.
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