In order to improve the detection ability of low,slow and small unmanned aerial vehicle(UAV)targets with very small pixels in dynamic,wide-angle scenes,this paper proposes a detection method that integrates inter frame information with template matching.Firstly,a dynamic information extraction module was designed to guide the algorithm to focus on dynamically changing small target areas by filtering out background information interference.Secondly,a multi template matching strategy is adopted to determine the similarity of the selected dynamic regions and complete drone target detection.Finally,drone target detection experiments were conducted under different backgrounds such as sky,mountains,and buildings,with different sizes and modes.The results show that the method proposed in this paper can effectively compensate for the shortcomings of deep learning methods in detecting extremely small pixel targets in wide-angle views.The detection accuracy of low,slow and small targets reaches 0.81,with a false alarm rate of 0.06,and the accuracy can reach 0.70 on datasets with pixel ratios not less than 0.01％.The method is suitable for data processing in different modes such as visible light and infrared,and can meet the application needs of various intelligent algorithm combinations for detection in the future.
关键词
动态场景/低慢小无人机探测/动态提取/空间匹配/极小像素检测
Key words
dynamic scenes/low slow small UAV detection/dynamic extraction/template matching/small pixel detection
维普
万方数据