A Gas Detection Method Based on Multiscale Infrared Image Semantic Segmentation

Jue Wang1; Yuxiang Lin2; Qi Zhao1; Dong Luo1; Wei He1; Shuaibao Chen3; Wei Chen1; Guohua Jiao1

10.1109/RCAR58764.2023.10250118

2023

979-8-3503-2719-9

2023 IEEE International Conference on Real-time Computing and Robotics (RCAR)

251-256

17-20 July 2023

Datong, China

Infrared imaging systems have been widely applied in gas leak detection. However, The existing gas detection methods have many limitations and are difficult to apply in real-world scenarios. At the same time, there are very few methods that combine gas detection and semantic segmentation with deep learning. In this study, a novel approach for gas detection using image semantic segmentation in deep learning is proposed. This method presents a new multi-scale semantic segmentation model named PUNet, based on PSPNet and U-Net, for automatic segmentation of infrared gas leakage images. Meanwhile, to solve the problems of single scene and fixed leakage location in the gas leakage image dataset, we added more self-collected infrared gas leakage images to the existing dataset. The experimental findings demonstrate that PUNet has higher accuracy than traditional foreground segmentation algorithm and outperforms the conventional U-Net model in segmenting gas leakage images, and exhibits enhanced efficacy in handling multi-scale gas leakage scenarios.

Deep learning Semantic segmentation Infrared imaging Feature extraction Prediction algorithms Data processing Real-time systems

其他

EI

20234214880542

Deep learning ; Gas detectors ; Gases ; Infrared imaging ; Leak detection ; Learning systems ; Semantic Segmentation ; Semantics

Ergonomics and Human Factors Engineering:461.4 ; Artificial Intelligence:723.4 ; Imaging Techniques:746 ; Accidents and Accident Prevention:914.1 ; Special Purpose Instruments:943.3

IEEE

1.Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
2.Shenzhen Technology University, Shenzhen Guangdong, China
3.College of Engineering, Southern University of Science and Technology, Shenzhen, China

Jue Wang,Yuxiang Lin,Qi Zhao,et al. A Gas Detection Method Based on Multiscale Infrared Image Semantic Segmentation[C],2023:251-256.