Real-time Water Quality Monitoring System Using Vision Camera and Multiple Objects Tracking Method 


Vol. 32,  No. 4, pp. 401-410, Apr.  2007


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  Abstract

In this paper, we propose water quality monitoring system using vision camera and multiple objects tracking method. The proposed system analyzes object individually using vision camera unlike monitoring system using sensor method. The system using vision camera consists of individual object segmentation part and objects tracking part based on interrelation between successive frames. For real-time processing, we make background image using non-parametric estimation and extract objects using background image. If we use non-parametric estimation, objects extraction method can reduce large amount of computation complexity, as well as extract objects more effectively. Multiple objects tracking method predicts next motion using moving direction, velocity and acceleration of individual object then carries out tracking based on the predicted motion. And we apply exception handling algorithms to improve tracking performance. From experiment results under various conditions, it shows that the proposed system can be available for real-time water quality monitoring system since it has very short processing time and correct multiple objects tracking.

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  Cite this article

[IEEE Style]

W. Yang, J. Lee, I. Cho, J. Jin, D. Jeong, "Real-time Water Quality Monitoring System Using Vision Camera and Multiple Objects Tracking Method," The Journal of Korean Institute of Communications and Information Sciences, vol. 32, no. 4, pp. 401-410, 2007. DOI: .

[ACM Style]

Won-Keun Yang, Jung-Ho Lee, Ik-Hwan Cho, Ju-Kyong Jin, and Dong-Seok Jeong. 2007. Real-time Water Quality Monitoring System Using Vision Camera and Multiple Objects Tracking Method. The Journal of Korean Institute of Communications and Information Sciences, 32, 4, (2007), 401-410. DOI: .

[KICS Style]

Won-Keun Yang, Jung-Ho Lee, Ik-Hwan Cho, Ju-Kyong Jin, Dong-Seok Jeong, "Real-time Water Quality Monitoring System Using Vision Camera and Multiple Objects Tracking Method," The Journal of Korean Institute of Communications and Information Sciences, vol. 32, no. 4, pp. 401-410, 4. 2007.