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	Bakgrundssubtraktion	Morfologisk bildbehandling
Ämnesområde	Datorseende	Datorseende
Familj	Machine learning	Machine learning
Ursprungsår	1999	1982
Upphovsperson	Stauffer and Grimson	Jean Serra
Typ	Temporal image analysis	Set theory and topological image processing
Ursprungskälla	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.	Serra, J. (1982). Image Analysis and Mathematical Morphology. Academic Press.
Alias	Foreground detection, Video segmentation	Mathematical morphology, Morphological filtering
Närliggande	5	5
Sammanfattning	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.	Morphological image processing, introduced by Jean Serra in 1982, is a technique based on set theory that reshapes and analyzes image regions using geometric structuring elements. Core operations include erosion and dilation, which can be combined into more complex operations like opening and closing, enabling noise removal, edge detection, and object analysis.