中北大学学报（自然科学版）2025，Vol.46Issue(5)：574-583,10.DOI:10.62756/jnuc.issn.1673-3193.2024.12.0014
基于边缘增强和通道重建的气体泄漏红外图像分割算法
Infrared Image Segmentation Algorithm for Gas Leakage Based on Edge Enhancement and Channel Reconstruction
摘要
Abstract
Aiming at the problems of low contrast and fuzzy edges of infrared images of leaking gas,this paper proposed a segmentation algorithm for infrared images of gas leakage based on edge enhancement and channel reconstruction.It was optimized on the AP-UNet architecture.Firstly,spatial and channel reconstruction convolution(SCConv)was used as a lightweight strategy to replace the standard convolu-tion operation,which reduced the computational redundancy and improved the detection real-time perfor-mance.Secondly,an edge guidance module(EGM)was designed and integrated to accurately capture the edge details of the leaking gas,which ensured that the tiny boundaries of the leaking gas could be accu-rately recognized and segmented under complex environments and low contrast conditions,thus improved the accuracy and robustness of the detection.In addition,the model used spatial convolution to obtain the inter-frame features of the video,and learned the gas motion law to improve the detection accuracy.The experimental results on the GasVid dataset show that the Dice coefficient,recall rate,and F1 score of the algorithm in this paper reach 77.8%,94.1%,and 90.8%,respectively,which are 1.4,3.4,and 0.8 percentage points higher than those of the baseline network.The inference speed reaches 25.2 frames per second,meeting the requirements of real-time detection.The method in this paper can realize high-precision leakage detection,which is better than the detection accuracy of most models,and can be better applied to gas leakage scenarios in complex environments.关键词
气体泄漏检测/轻量化/边缘增强/帧间特征/目标分割Key words
gas leakage detection/lightweight strategy/edge enhancement/inter-frame features/object segmentation分类
信息技术与安全科学引用本文复制引用
胡亚蕾,秦品乐,柴锐,曾建潮..基于边缘增强和通道重建的气体泄漏红外图像分割算法[J].中北大学学报（自然科学版）,2025,46(5):574-583,10.基金项目
山西省科技重大专项计划"揭榜挂帅"项目(202101010101018) （202101010101018）
