Global illumination invariant object detection with level set based bimodal segmentation

Suk Ho Lee; Hyenkyun Woo; Moon Gi Gi Kang

doi:10.1109/TCSVT.2010.2041824

Global illumination invariant object detection with level set based bimodal segmentation

Suk Ho Lee, Hyenkyun Woo, Moon Gi Gi Kang

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

In this letter, we propose a new 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 charge coupled device (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, changes in contrast, and noise level.

Original language	English
Article number	5401108
Pages (from-to)	616-620
Number of pages	5
Journal	IEEE Transactions on Circuits and Systems for Video Technology
Volume	20
Issue number	4
DOIs	https://doi.org/10.1109/TCSVT.2010.2041824
Publication status	Published - 2010 Apr

Bibliographical note

Funding Information:
Manuscript received December 8, 2008; revised June 8, 2009. First version published January 29, 2010; current version published April 2, 2010. This work was supported by the IT Research and Development Program of MKE/MCST/IITA (2008-F-031-01, Development of Computational Photography Technologies for Image and Video Contents) and the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education, Science and Technology (2009-0079024). This letter was recommended by Associate Editor L. Guan.

All Science Journal Classification (ASJC) codes

Media Technology
Electrical and Electronic Engineering

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10.1109/TCSVT.2010.2041824

Cite this

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abstract = "In this letter, we propose a new 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 charge coupled device (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, changes in contrast, and noise level.",

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note = "Funding Information: Manuscript received December 8, 2008; revised June 8, 2009. First version published January 29, 2010; current version published April 2, 2010. This work was supported by the IT Research and Development Program of MKE/MCST/IITA (2008-F-031-01, Development of Computational Photography Technologies for Image and Video Contents) and the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education, Science and Technology (2009-0079024). This letter was recommended by Associate Editor L. Guan.",

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Global illumination invariant object detection with level set based bimodal segmentation

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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