An Effective Method for Gas-Leak Area Detection and Gas Identification with Mid-Infrared Image

Zhao, Qi1,2; Nie, Xiaoxi2,3; Luo, Dong2; Wang, Jue1,2; Li, Qiran2; Chen, Wei2

2022-12-01

10.3390/photonics9120992

PHOTONICS   Impact Factor & Quartile

2304-6732

Mid-infrared imaging systems are widely applied in gas-leak detection. However, infrared images generally suffer from low contrast and poor quality. In this paper, an image-enhancement method based on Gaussian filtering and adaptive histogram segmentation is proposed to effectively improve the quality of infrared images. It can effectively improve the quality of infrared images, which contributes to the subsequent gas-image feature extraction. The traditional background modeling algorithm is analyzed, and the ViBe (visual background extractor) algorithm is studied in depth. Based on the advantages and disadvantages of the ViBe algorithm and the characteristics of gas-leak images, a gas-leak region detection method based on the improved ViBe algorithm is proposed. The test results show that it can quickly establish a background model, segment the gas-leak region with motion characteristics, and render the gas-leak region in color based on grayscale mapping to achieve the automatic detection and enhanced display of gas leaks.

gas leakage infrared imaging image enhancement background extraction

SCI

English

First

Key-Area Research and Development Program of Guangdong Province[2019B111102003] ; Youth Innovation Promotion Association CAS and International Collaborative Research Program[GJHZ20210705141403009]

Optics

Optics

WOS:000904475200001

MDPI

Web of Science

1.Southern Univ Sci & Technol, Coll Engn, 1088 Xueyuan Ave, Shenzhen 518055, Peoples R China
2.Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China
3.Univ Elect Sci & Technol China, Sch Resources & Environm, Chengdu 611731, Peoples R China

Zhao, Qi,Nie, Xiaoxi,Luo, Dong,et al. An Effective Method for Gas-Leak Area Detection and Gas Identification with Mid-Infrared Image[J]. PHOTONICS,2022,9(12).

Zhao, Qi,Nie, Xiaoxi,Luo, Dong,Wang, Jue,Li, Qiran,&Chen, Wei.(2022).An Effective Method for Gas-Leak Area Detection and Gas Identification with Mid-Infrared Image.PHOTONICS,9(12).

Zhao, Qi,et al."An Effective Method for Gas-Leak Area Detection and Gas Identification with Mid-Infrared Image".PHOTONICS 9.12(2022).