Title
An adaptive motion segmentation for automated video surveillance
Abstract
This paper presents an adaptive motion segmentation algorithm utilizing spatiotemporal information of three most recent frames. The algorithm initially extracts the moving edges applying a novel flexible edge matching technique which makes use of a combined distance transformation image. Then watershed-based iterative algorithm is employed to segment the moving object region from the extracted moving edges. The challenges of existing three-frame-based methods include slow movement, edge localization error, minor movement of camera, and homogeneity of background and foreground region. The proposed method represents edges as segments and uses a flexible edge matching algorithm to deal with edge localization error and minor movement of camera. The combined distance transformation image works in favor of accumulating gradient information of overlapping region which effectively improves the sensitivity to slow movement. The segmentation algorithm uses watershed, gradient information of difference image, and extracted moving edges. It helps to segment moving object region with more accurate boundary even some part of the moving edges cannot be detected due to region homogeneity or other reasons during the detection step. Experimental results using different types of video sequences are presented to demonstrate the efficiency and accuracy of the proposed method.
Year
DOI
Venue
2008
10.1155/2008/187413
EURASIP J. Adv. Sig. Proc.
Field
DocType
Volume
Computer vision,Signal processing,Segmentation,Computer science,Edge detection,Iterative method,Image processing,Image segmentation,Artificial intelligence,Adaptive algorithm,Motion estimation
Journal
2008,
Issue
ISSN
Citations 
187413
1687-6180
2
PageRank 
References 
Authors
0.38
20
3
Name
Order
Citations
PageRank
M. Ali Akber Dewan1799.53
M. Julius Hossain2739.50
Oksam Chae361646.52