Scene segmentation based on IPCA for visual surveillance
Neurocomputing
A novel iris segmentation using radial-suppression edge detection
Signal Processing
A fast approach of object segmentation for video sequence
SIP '07 Proceedings of the Ninth IASTED International Conference on Signal and Image Processing
Shadows Removal by Edges Matching
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Edge-Based Algorithm for Shadows and Ghosts Removing
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Shadow detection in video surveillance by maximizing agreement between independent detectors
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Adaptive shadow estimator for removing shadow of moving object
Computer Vision and Image Understanding
Signal Processing
Aurora image segmentation by combining patch and texture thresholding
Computer Vision and Image Understanding
A survey of cast shadow detection algorithms
Pattern Recognition Letters
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To prevent moving cast shadows from being misunderstood as part of moving objects in change detection based video segmentation, this paper proposes a novel approach to the cast shadow detection based on the edge and region information in multiple frames. First, an initial change detection mask containing moving objects and cast shadows is obtained. Then a Canny edge map is generated. After that, the shadow region is detected and removed through multiframe integration, edge matching, and region growing. Finally, a post processing procedure is used to eliminate noise and tune the boundaries of the objects. Our approach can be used for video segmentation in indoor environment. The experimental results demonstrate its good performance.