Unmanned Aerial Vehicle Target Detection Method Based on Combined Infrared and Visible LightOA
Visible light cameras are excellent at capturing subtle features of moving targets in well⁃wit and stable scenes.However,such cameras may not be able to accurately detect targets when encountering occlusion,fluctuating light intensity,or shadow effects,leading to the occurrence of missed or false alarms.Aiming at the problem of poor anti⁃interference ability of visible light images in complex scenes,a target detection method based on the combination of visible light and infrared images is proposed.The Canny algorithm is used to preprocess the unmanned aerial vehicle(UAV)infrared image,the seed points are obtained through the Sobel operator,and the image segmentation is performed using the maximum inter⁃class variance value of the image as the growth criterion in order to locate the UAV region in the infrared image.Then the corresponding region of the visible image is cropped,and UAV target detection is performed in this region.The joint detection method narrows the scope of detection and effectively reduces the interference of factors such as illumination changes and interfering objects on the detection results.Experimental results show that the proposed method achieves 87.6%precision and 75.9%recall,with mAP0.5 and mAP0.5:0.95 values of 83.9%and 52.9%,respectively.
XU Song;JI Guipeng;ZHAO Hongsheng;YU Tengli;WANG Ershen;QU Pingping;CHEN Yunhao;ZHANG Hongxuan
College of Electronic and Information Engineering,Shenyang Aerospace University,Shenyang 110136,P.R.China State Key Laboratory of Extreme Environment Optoelectronic Dynamic Testing Technology and Instrument,North University of China,Taiyuan 030051,P.R.ChinaCollege of Aerospace Engineering,Shenyang Aerospace University,Shenyang 110136,P.R.ChinaChinese Aeronautical Radio Electronics Research Institute,Aviation Industry Corporation of China,Shanghai 200233,P.R.ChinaCollege of Aerospace Engineering,Shenyang Aerospace University,Shenyang 110136,P.R.ChinaCollege of Electronic and Information Engineering,Shenyang Aerospace University,Shenyang 110136,P.R.China College of Civil Aviation,Shenyang Aerospace University,Shenyang 110136,P.R.ChinaCollege of Electronic and Information Engineering,Shenyang Aerospace University,Shenyang 110136,P.R.ChinaCollege of Electrical and Information Engineering,Yunnan Minzu University,Kunming 650500,P.R.China Yunnan Key Laboratory of Unmanned Autonomous Systems,Yunnan Minzu University,Kunming 650500,P.R.ChinaCollege of Electronic and Information Engineering,Shenyang Aerospace University,Shenyang 110136,P.R.China
信息技术与安全科学
UAV target detectioninfrared imagevisible imageimage conjunctionYOLOv5 algorithm
《Transactions of Nanjing University of Aeronautics and Astronautics》 2026 (3)
P.400-411,12
supported by the Open Fund of State key Laboratory of Extreme Environment Optoelectronic Dynamic Testing Technology and Instrument,North University of China(No.2023⁃SYSJJ⁃04)the Aeronautical Science Foundation of China(No.20240055054001)the Open Fund of Key Laboratory of Spatio⁃temporal Sensing and Intelligent Processing,Ministry of Natural Resources of the People’s Republic of China(No.232203)the Open Fund of Key Laboratory of Technology and Equipment of Tianjin Urban Air Transportation System(No.TJKL-UAM-202305)the Open Fund of Key Laboratory of Civil Aviation Flights Wide Area Surveillance and Safety Control technology of Civil Aviation University of China(No.202105)the Open Fund of Key Laboratory of Flight Techniques and Flight Safety CAAC(No.FZ2021KF15).
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