Connected-component labeling
Connected-component labeling (CCL), connected-component analysis (CCA), 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, but it can be applicable to gray-scale and color images as well. Blobs may be counted, filtered, and tracked.
Blob extraction is related to but distinct from blob detection.
레이블링은 객체 구역을 영역 단위로 분석하는 것입니다. 서로 연결되어 있는 객체 픽셀에 고유한 번호를 지정하는 작업입니다. (레이블맵) 일반적으로 이진 영상에서 수행합니다. 레이블링 속도가 외곽선 검출보다 빨라서 더 효율적입니다.