방법 비교

	배경 차분	산계 분할
분야	컴퓨터 비전	컴퓨터 비전
계열	Machine learning	Machine learning
기원 연도	1999	1979
창시자	Stauffer and Grimson	Serge Beucher and Christian Lantuéjoul
유형	Temporal image analysis	Morphological image segmentation
원전	Stauffer, C., & Grimson, W. E. L. (1999). Adaptive background mixture models for real-time tracking. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 246–252.	Meyer, F. (1994). Topographic distance and watershed lines. Signal Processing, 38(1), 113–125.
별칭	Foreground detection, Video segmentation	Watershed transform, Water shedding segmentation
관련	5	5
요약	Background subtraction is a video processing technique that separates moving foreground objects from a static or slowly changing background by comparing each frame to a learned or estimated background model. Widely used in video surveillance and motion detection, background subtraction enables robust foreground detection even in complex scenes with illumination changes.	Watershed segmentation is a morphological image processing technique that automatically segments an image into distinct regions by treating image intensity as a topographic landscape where each object corresponds to a valley. Introduced by Beucher and Lantuéjoul in 1979 and refined by Meyer, the watershed algorithm is particularly effective for separating touching or overlapping objects.