Image difference threshold strategies and shadow detection
BMVC '95 Proceedings of the 1995 British conference on Machine vision (Vol. 1)
Detecting Moving Shadows: Algorithms and Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cast shadow segmentation using invariant color features
Computer Vision and Image Understanding
Robust and Efficient Foreground Analysis for Real-Time Video Surveillance
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Shadow detection for moving objects based on texture analysis
Pattern Recognition
Learning and Removing Cast Shadows through a Multidistribution Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning to Detect Moving Shadows in Dynamic Environments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient background subtraction and shadow removal for monochromatic video sequences
IEEE Transactions on Multimedia - Special section on communities and media computing
Moving Cast Shadows Detection Using Ratio Edge
IEEE Transactions on Multimedia
Detecting moving objects, ghosts, and shadows in video streams
IEEE Transactions on Pattern Analysis and Machine Intelligence
Insignificant shadow detection for video segmentation
IEEE Transactions on Circuits and Systems for Video Technology
| Hi-index | 0.00 |
Visual surveillance is often based on background subtraction; it usually detects moving regions in a rough way, with the presence of shadows, ghosts and reflections. In order to improve quality of segmented objects by removing these artifacts in this work we propose an approach based on edge matching. The basic idea is that edges extracted in shadow (or ghost) regions in current image exactly match with edges extracted in the same regions in the background image. On the contrary, edges extracted on foreground objects have not correspondent edges in the background image. A preliminary segmentation procedure based on the uniformity of photometric gain between adjacent points has been carried out to allow a better shadow removing. The algorithm has been tested in many different real contexts, both in indoor and outdoor context.