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Connected-component labeling
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<p>Connected-component labeling (CCL), connected-component analysis (CCA), blob extraction, region labeling, blob discovery, or region extraction is an algorithmic application of <a href="/facts/Graph_theory/VVPCd4TX">graph theory</a>, where subsets of <a href="/facts/Connected_component_(graph_theory)/5owVSXtY">connected components</a> are uniquely labeled based on a given <a href="/facts/Heuristic/BcBEkv9c">heuristic</a>. Connected-component labeling is not to be confused with <a href="/facts/Segmentation_(image_processing)/jofAhbxa">segmentation</a>. </p><p>Connected-component labeling is used in <a href="/facts/Computer_vision/Tl2Yyk66">computer vision</a> to detect connected <a href="/facts/Region/CdM1oaR3">regions</a> in <a href="/facts/Binary_image/qaKaPntY">binary</a> <a href="/facts/Digital_image/3TNT47Mv">digital images</a>, although <a href="/facts/Color_image/u5oW73uC">color images</a> and data with higher dimensionality can also be processed. When integrated into an <a href="/facts/Image_recognition/Tl2Yyk66">image recognition</a> system or <a href="/facts/Human-computer_interaction/EkmIxGCx">human-computer interaction</a> interface, connected component labeling can operate on a variety of information. Blob extraction is generally performed on the resulting <a href="/facts/Binary_image/qaKaPntY">binary image</a> from a thresholding step, but it can be applicable to gray-scale and color images as well. Blobs may be counted, filtered, and tracked. </p><p>Blob extraction is related to but distinct from <a href="/facts/Blob_detection/F5yCn3eQ">blob detection</a>. </p>