Motion detection with level set-based segmentation

Suk Ho Lee; Nam Seok Choi; Moon Gi Kang

doi:10.1117/12.839159

Motion detection with level set-based segmentation

Suk Ho Lee, Nam Seok Choi, Moon Gi Kang

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we propose a level set based object detection method for video surveillance which provides for a robust and real-time working object detection under various global illumination conditions. The proposed scheme needs no manual parameter settings for different illumination conditions, which makes the algorithm applicable to automatic surveillance systems. Two special filters are designed to eliminate the spurious object regions that occur due to the CCD noise, making the scheme stable even in very low illumination conditions. We demonstrate the effectiveness of the proposed algorithm experimentally with different illumination conditions, change of contrast, and noise level.

Original language	English
Title of host publication	Proceedings of SPIE-IS and T Electronic Imaging - Image Processing
Subtitle of host publication	Machine Vision Applications III
DOIs	https://doi.org/10.1117/12.839159
Publication status	Published - 2010
Event	Image Processing: Machine Vision Applications III - San Jose, CA, United States Duration: 2010 Jan 19 → 2010 Jan 21

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	7538
ISSN (Print)	0277-786X

Other

Other	Image Processing: Machine Vision Applications III
Country	United States
City	San Jose, CA
Period	10/1/19 → 10/1/21

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

Access to Document

10.1117/12.839159

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Cite this

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title = "Motion detection with level set-based segmentation",

abstract = "In this paper, we propose a level set based object detection method for video surveillance which provides for a robust and real-time working object detection under various global illumination conditions. The proposed scheme needs no manual parameter settings for different illumination conditions, which makes the algorithm applicable to automatic surveillance systems. Two special filters are designed to eliminate the spurious object regions that occur due to the CCD noise, making the scheme stable even in very low illumination conditions. We demonstrate the effectiveness of the proposed algorithm experimentally with different illumination conditions, change of contrast, and noise level.",

author = "Lee, {Suk Ho} and Choi, {Nam Seok} and Kang, {Moon Gi}",

year = "2010",

doi = "10.1117/12.839159",

language = "English",

isbn = "9780819479310",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

booktitle = "Proceedings of SPIE-IS and T Electronic Imaging - Image Processing",

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Lee, SH, Choi, NS & Kang, MG 2010, Motion detection with level set-based segmentation. in Proceedings of SPIE-IS and T Electronic Imaging - Image Processing: Machine Vision Applications III., 75380O, Proceedings of SPIE - The International Society for Optical Engineering, vol. 7538, Image Processing: Machine Vision Applications III, San Jose, CA, United States, 10/1/19. https://doi.org/10.1117/12.839159

Motion detection with level set-based segmentation. / Lee, Suk Ho; Choi, Nam Seok; Kang, Moon Gi.

Proceedings of SPIE-IS and T Electronic Imaging - Image Processing: Machine Vision Applications III. 2010. 75380O (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 7538).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - In this paper, we propose a level set based object detection method for video surveillance which provides for a robust and real-time working object detection under various global illumination conditions. The proposed scheme needs no manual parameter settings for different illumination conditions, which makes the algorithm applicable to automatic surveillance systems. Two special filters are designed to eliminate the spurious object regions that occur due to the CCD noise, making the scheme stable even in very low illumination conditions. We demonstrate the effectiveness of the proposed algorithm experimentally with different illumination conditions, change of contrast, and noise level.

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