Visualization and Evaluation of Methane Gas Leakage by Thermal Image Processing Using Supervised Deep Learning Models

Sowndarya, G. S.; Shanthi, C.

doi:10.1007/978-981-16-2674-6_15

Cited by 1 publication

(2 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to make the generated target image close to the infrared thermal imaging target feature, it is necessary to carry out image morphological processing on it. In this paper, selecting circular structural elements can more effectively smooth the target edge, and the selection of radius r varies from [5,9] according to the characteristics of the actual image. If X is the target image and B is the structural element, then the corrosion operation of B on X is defined as:…”

Section: S X Y R X Y G X Y B X Y R X Y G X Y B X Ymentioning

confidence: 99%

“…Infrared thermal imaging technology was first applied in the military field. With the gradual decline of the cost of infrared detectors, especially uncooled infrared detectors, researchers began to use infrared thermal imaging technology to monitor specific places in petrochemical areas [4][5][6] . More and more manufacturers of infrared thermal imaging and security monitoring products have also expanded the product line of infrared thermal imaging security monitoring in petrochemical areas.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Fire detection algorithm of infrared thermal imaging in petrochemical area based on improved YOLOv4-tiny framework and time-domain feature analysis

Ma¹,

Zhao²,

Sun³

et al. 2023

Conference on Infrared, Millimeter, Terahertz Waves and Applications (IMT2022)

View full text Add to dashboard Cite

Oil is one of the most important energy supplies for economic development. In recent years, the fire safety problems of petrochemical enterprises have become prominent, with serious casualties and property losses. The continuously monitoring of key areas through the low-cost and intelligent infrared thermal imaging video monitoring system has important engineering application significance for the improvement of petrochemical site safety problems. According to the characteristics of infrared thermal imaging fire target, this paper proposes a method of deep neural network combined with time-domain feature analysis to realize fire detection. Firstly, high thermal pixels are extracted from the infrared image, and the gray-scale image is converted into a binary gray-scale image. Based on the YOLOv4 tiny framework, multi-level channel prediction and attention mechanism are added to detect the fire candidate target of the binary image, Finally, the candidate target is finally determined by analyzing the time-domain characteristics. Compared with the traditional temperature threshold judgment infrared temperature measurement fire alarm system, it can achieve high detection rate and effectively reduce the false alarm rate of the system. The intelligent security monitoring system in Petrochemical area designed in this paper has been applied in practical engineering, and the fire detection effect is good, which realizes the requirements of low power consumption, low cost and high reliability of the security monitoring system in Petrochemical area based on infrared thermal imaging.

show abstract

Section: S X Y R X Y G X Y B X Y R X Y G X Y B X Ymentioning

confidence: 99%

mentioning

confidence: 99%