# Connected Component Analysis

Identifies connected components in an image.

Connected component labeling (alternatively connected component analysis) is an algorithmic application of graph theory, where subsets of connected components are uniquely labeled. Connected component labeling is used in computer vision to detect connected regions in binary digital images.

A graph, containing vertices and connecting edges, is constructed from relevant input data. The vertices contain information required by the comparison heuristic, while the edges indicate connected 'neighbors'. An algorithm traverses the graph, labeling the vertices based on the connectivity and relative values of their neighbors. Connectivity is determined by the medium; image graphs, for example, can be 4-connected or 8-connected.

### Input Ports

- Type: Data Images

### Output Ports

- Type: Data Labeled segments

## Short Link

Drag node into KNIME Analytics Platform