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PodručjeRačunalni vidRačunalni vid
ObiteljMachine learningMachine learning
Godina nastanka19991985
TvoracStauffer and GrimsonSatoshi Suzuki and Keiichi Abe
VrstaTemporal image analysisShape and contour analysis
Temeljni izvorStauffer, 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. DOI ↗Suzuki, S., & Abe, K. (1985). Topological structural analysis of digitized binary images by border following. Computer Vision, Graphics, and Image Processing, 30(1), 32–46. DOI ↗
Drugi naziviForeground detection, Video segmentationEdge-based contours, Boundary analysis
Srodne55
SažetakBackground 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.Contour analysis is the process of detecting and analyzing the boundaries of objects in images by identifying connected edges and extracting shape information. The Suzuki-Abe algorithm provides an efficient method for finding contours in binary images, enabling shape-based object classification and segmentation.
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  1. v1
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  3. PUBLISHED

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ScholarGateUsporedite metode: Background Subtraction · Contour Analysis. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare