Title | An Effective Method for Gas-Leak Area Detection and Gas Identification with Mid-Infrared Image |
Author | |
Corresponding Author | Chen, Wei |
Publication Years | 2022-12-01
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DOI | |
Source Title | |
EISSN | 2304-6732
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Volume | 9Issue:12 |
Abstract | 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. |
Keywords | |
URL | [Source Record] |
Indexed By | |
Language | English
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SUSTech Authorship | First
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Funding Project | Key-Area Research and Development Program of Guangdong Province[2019B111102003]
; Youth Innovation Promotion Association CAS and International Collaborative Research Program[GJHZ20210705141403009]
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WOS Research Area | Optics
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WOS Subject | Optics
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WOS Accession No | WOS:000904475200001
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Publisher | |
Data Source | Web of Science
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Citation statistics |
Cited Times [WOS]:2
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Document Type | Journal Article |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/424795 |
Department | College of Engineering |
Affiliation | 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 |
First Author Affilication | College of Engineering |
First Author's First Affilication | College of Engineering |
Recommended Citation GB/T 7714 |
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).
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APA |
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).
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MLA |
Zhao, Qi,et al."An Effective Method for Gas-Leak Area Detection and Gas Identification with Mid-Infrared Image".PHOTONICS 9.12(2022).
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