jinzhu6/cuda-connected-component-labelling

Parallel GPU Implementation of Connected Component Labelling (CCL). Connected-component labeling is used in computer vision to detect connected regions in binary digital images

CUDA-Connected-Component-Labelling

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 used in computer vision to detect connected regions in binary digital images, although color images and data with higher dimensionality can also be processed.

For example, in problems where we have images like these -

When integrated into an connected component labeling can operate on a variety of information. B image recognition system or human-computer interaction interface,lob extraction is generally performed on the resulting binary image from a thresholding step.

Blobs may be counted, filtered, and tracked. Considering the prominence of Connected Component Labelling and its applications, an approach towards speeding up its execution has been made by a parallel GPU based implementation.