Paper
29 January 1999 Video-based automatic surveillance of oil leaks in a power plant by using artificial neural networks
T. Ogawa, Koichi Ogawa, Hidehiro Uekusa, Minoru Mukasa, J. Momii
Author Affiliations +
Proceedings Volume 3584, 27th AIPR Workshop: Advances in Computer-Assisted Recognition; (1999) https://doi.org/10.1117/12.339832
Event: The 27th AIPR Workshop: Advances in Computer-Assisted Recognition, 1998, Washington, DC, United States
Abstract
A new technique for the detection of oil leaks in a power plant is presented which is based on artificial neural networks. In this system the neural network was trained by feature parameters extracted from ITV images of the normal condition and oil leaks. For input data in the neural network we used four parameters calculated from two regions of interest in a subsequent image. They were the rate of variation of pixel values, variance of the pixel values, skewness of the pixel values and rate of variation of the skewness. The results showed that the accuracies of recognition were more than about 90%. The system is considered to be helpful for industrial surveillance application.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
T. Ogawa, Koichi Ogawa, Hidehiro Uekusa, Minoru Mukasa, and J. Momii "Video-based automatic surveillance of oil leaks in a power plant by using artificial neural networks", Proc. SPIE 3584, 27th AIPR Workshop: Advances in Computer-Assisted Recognition, (29 January 1999); https://doi.org/10.1117/12.339832
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KEYWORDS
Neural networks

Surveillance

Artificial neural networks

Surveillance systems

Cameras

Video

Video surveillance

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