Related papers: Computer Vision-based Characterization of Large-scale Jet Flames using a Synthetic Infrared Image Generation Approach

Computer Vision-based Characterization of Large-scale Jet Flames using a Synthetic Infrared Image Generation Approach

URL: http://arxiv.org/abs/2206.02110v1
Date: Sun, 5 Jun 2022 06:54:36 GMT
Title: Computer Vision-based Characterization of Large-scale Jet Flames using a Synthetic Infrared Image Generation Approach
Authors: Carmina P\'erez-Guerrero, Jorge Francisco Cipri\'an-S\'anchez, Adriana Palacios, Gilberto Ochoa-Ruiz, Miguel Gonzalez-Mendoza, Vahid Foroughi, Elsa Pastor, Gerardo Rodriguez-Hernandez
Abstract summary: This paper proposes the use of Generative Adversarial Networks to produce plausible infrared images from visible ones. Results suggest that it is possible to realistically replicate the results for experiments carried out using both visible and infrared cameras.
Score: 0.8431877864777444
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Among the different kinds of fire accidents that can occur during industrial activities that involve hazardous materials, jet fires are one of the lesser-known types. This is because they are often involved in a process that generates a sequence of other accidents of greater magnitude, known as domino effect. Flame impingement usually causes domino effects, and jet fires present specific features that can significantly increase the probability of this happening. These features become relevant from a risk analysis perspective, making their proper characterization a crucial task. Deep Learning approaches have become extensively used for tasks such as jet fire characterization; however, these methods are heavily dependent on the amount of data and the quality of the labels. Data acquisition of jet fires involve expensive experiments, especially so if infrared imagery is used. Therefore, this paper proposes the use of Generative Adversarial Networks to produce plausible infrared images from visible ones, making experiments less expensive and allowing for other potential applications. The results suggest that it is possible to realistically replicate the results for experiments carried out using both visible and infrared cameras. The obtained results are compared with some previous experiments, and it is shown that similar results were obtained.

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