红外技术2024，Vol.46Issue(3)：325-331,7.
基于运动与模糊特征的红外热成像烟雾检测
Infrared Thermal Imaging Smoke Detection Based on Motion and Fuzzy Features
摘要
Abstract
The production process of coking enterprises generates abundant smoke.Their discharge and leakage can pollute the natural environment,endangering the safety of life and production.Considering the low contrast and poor texture of thermal imaging videos,this study detected smoke with motion and fuzzy characteristics.The noise degree of each frame image can be calculated to replace the fixed threshold of the Vibe detection algorithm so that the moving target area can be completely detected.First,the image was divided into block area images;then,the fuzzy-to-noise ratio in this area was extracted by combining the motion area,the features calculated when the fast fourier transform(FFT)was used to calculate the ambiguity were trained to generate a smoke classifier,and finally,the experimental video detection,with an average accuracy rate of 94.53%.The results show that the proposed algorithm is accurate,operates in real-time for smoke detection in infrared thermal imaging videos of coking enterprises,and has good anti-interference ability.关键词
改进Vibe模糊烟雾特征/红外热成像/烟雾检测Key words
improved Vibe fuzzy smoke features/infrared thermal imaging/smoke detection分类
信息技术与安全科学引用本文复制引用
李咸静,郝争辉..基于运动与模糊特征的红外热成像烟雾检测[J].红外技术,2024,46(3):325-331,7.基金项目
山西省高等学校科技创新计划项目(2023L323)资助. （2023L323）
