A knowledge based infrared camera system for invisible gas detection utilizing image processing techniques

Hyungjun Kim

doi:10.1007/s12652-019-01342-x

Abstract

An infrared camera system for real-time monitoring of invisible methane gas leakages is proposed, which can be used in production, transportation, and gas plants. Instead of using conventional lasers, a medium wavelength light-emitting diode (LED) with a center wavelength of approximately 3300 nm is used for the light source of the gas detector. We achieve compact cooling with low power consumption by using a small electronic part with a Peltier element instead of a larger cooling unit. We also propose an algorithm based on adaptive average method and adaptive histogram equalization process to extract the background efficiently. This knowledge based infrared camera system effectively detects the leakage of invisible gas. Preliminary experimental results confirm the potential and effectiveness of the developed equipment to be commercialized for use in real-time gas monitoring systems. We aim to eventually develop an image analysis system that combines image processing and knowledge engineering techniques.

Highlights

In this paper, we propose an infrared camera system that analyzes image sequence from a camera to detect invisible leakage of gas
We proposed an infrared camera system that analyzes image sequences to detect invisible gas leaks
To increase the mobility of infrared cameras, instead of using laser as in conventional methane gas detectors, a medium wavelength light-emitting diode (LED) with a center wavelength of approximately 3300 nm is used as the light source of the gas detector

Summary

Introduction

We propose an infrared camera system that analyzes image sequence from a camera to detect invisible leakage of gas. The proposed infrared camera equipment makes gas detection possible by means of digital image processing. One can monitor and prevent leakage of gas by using a camera instead of monitoring it directly at the spot. We apply an adaptive background extraction method to extract the background from the image. Because the camera for gas detection is stationary, we use the adaptive average method to detect background images. Once the background of the image is detected, the gas image can be extracted by subtracting the background from the input image. Because of the nature of gas images, the resolution of the output images is typically poor, requiring additional image processing to enhance the quality of the image. The following sections provide detailed descriptions of the algorithms mentioned here

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Methods

Conclusion