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  • Research Article
  • Open Access

Edge Segment-Based Automatic Video Surveillance

EURASIP Journal on Advances in Signal Processing20072008:743202

https://doi.org/10.1155/2008/743202

Received: 22 February 2007

Accepted: 1 October 2007

Published: 24 October 2007

Abstract

This paper presents a moving-object segmentation algorithm using edge information as segment. The proposed method is developed to address challenges due to variations in ambient lighting and background contents. We investigated the suitability of the proposed algorithm in comparison with the traditional-intensity-based as well as edge-pixel-based detection methods. In our method, edges are extracted from video frames and are represented as segments using an efficiently designed edge class. This representation helps to obtain the geometric information of edge in the case of edge matching and moving-object segmentation; and facilitates incorporating knowledge into edge segment during background modeling and motion tracking. An efficient approach for background initialization and robust method of edge matching is presented, to effectively reduce the risk of false alarm due to illumination change and camera motion while maintaining the high sensitivity to the presence of moving object. Detected moving edges are utilized along with watershed algorithm for extracting video object plane (VOP) with more accurate boundary. Experiment results with real image sequence reflect that the proposed method is suitable for automated video surveillance applications in various monitoring systems.

Keywords

  • Video Surveillance
  • Camera Motion
  • Illumination Change
  • Background Content
  • Edge Segment

Publisher note

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Authors’ Affiliations

(1)
Image Processing Lab, Department of Computer Engineering, Kyung Hee University, Yongin, South Korea

Copyright

© M. Julius Hossain et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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