An Adaptive Motion Segmentation for Automated Video Surveillance. (22nd March 2009)

• Record Type: Journal Article
• Authors: Dewan Dewan, M. Ali Akber M. Ali Akber; Hossain Hossain, M. Julius M. Julius; Chae Chae, Oksam Oksam
• Other Names: Tzovaras Tzovaras Dimitrios Dimitrios Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2009-03-22
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/187413
• Languages: English
• ISSNs: 1687-6172

Abstract

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.