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A block based moving object detection utilizing the distribution of noise

A block based moving object detection utilizing the distribution of noise
A block based moving object detection utilizing the distribution of noise

Moving object segmentation in complex scene is the basis for video surveillance, event detection, tracking and development of vision agent in industrial robotics. However, due to presence of camera noise and illumination change, simple background subtraction based techniques are not able to detect moving objects properly. In this paper, we present a novel block based moving object detection method which dynamically quests for both local and global properties of difference image to achieve robustness. Noise model of the difference image is determined analyzing the histogram of difference image and block wise local properties are computed. These local properties are compared with the noise model to extract moving blocks. To remove the stair like artifacts of the segmented result, and to obtain smoothed and accurate boundary, a refinement procedure is employed on the boundary regions of detected moving objects. Experimental results show that the proposed method is robust and achieves better performance in dynamic environment.

0302-9743
645-654
Springer
Dewan, M. Ali Akber
363af584-4a43-4a28-8f3c-25b78fbd5360
Hossain, M. Julius
bba1b875-7604-462b-a55b-ba0b54f728e8
Chae, Oksam
f3b49af7-329a-4eed-bcd1-33aa737cd234
Dewan, M. Ali Akber
363af584-4a43-4a28-8f3c-25b78fbd5360
Hossain, M. Julius
bba1b875-7604-462b-a55b-ba0b54f728e8
Chae, Oksam
f3b49af7-329a-4eed-bcd1-33aa737cd234

Dewan, M. Ali Akber, Hossain, M. Julius and Chae, Oksam (2007) A block based moving object detection utilizing the distribution of noise. In Agent and Multi-Agent Systems: Technologies and Applications - First KES International Symposium, KES-AMSTA 2007, Proceedings. vol. 4496 LNAI, Springer. pp. 645-654 . (doi:10.1007/978-3-540-72830-6_67).

Record type: Conference or Workshop Item (Paper)

Abstract

Moving object segmentation in complex scene is the basis for video surveillance, event detection, tracking and development of vision agent in industrial robotics. However, due to presence of camera noise and illumination change, simple background subtraction based techniques are not able to detect moving objects properly. In this paper, we present a novel block based moving object detection method which dynamically quests for both local and global properties of difference image to achieve robustness. Noise model of the difference image is determined analyzing the histogram of difference image and block wise local properties are computed. These local properties are compared with the noise model to extract moving blocks. To remove the stair like artifacts of the segmented result, and to obtain smoothed and accurate boundary, a refinement procedure is employed on the boundary regions of detected moving objects. Experimental results show that the proposed method is robust and achieves better performance in dynamic environment.

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More information

Published date: May 2007
Venue - Dates: 1st KES International Symposium on Agent and Multi-Agent Systems - Technologies and Applications, KES-AMSTA 2007, , Wroclaw, Poland, 2007-05-31 - 2007-06-01

Identifiers

Local EPrints ID: 467282
URI: http://eprints.soton.ac.uk/id/eprint/467282
ISSN: 0302-9743
PURE UUID: 5daedd85-9978-49d9-9866-6762660dfb3e
ORCID for M. Julius Hossain: ORCID iD orcid.org/0000-0003-3303-5755

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Date deposited: 05 Jul 2022 16:39
Last modified: 17 Mar 2024 04:12

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Contributors

Author: M. Ali Akber Dewan
Author: M. Julius Hossain ORCID iD
Author: Oksam Chae

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