Research on Automatic Target Detection Method for Aerial Photogrammetry Images of Coal Mine Geological Unmanned Aerial Vehicles
Image target detection is an important part of unmanned aerial vehicle aerial photogrammetry image processing,which can provide a basis for coal mine geological exploration decisions.However,the measurement images contain many small targets,and image object detection is difficult.Therefore,a method for automatic detection of targets in coal mine geological unmanned aerial vehicle aerial photogrammetry images is designed.This method uses spatial domain grayscale transformation to grayscale process the original measurement image,and applies mean filtering to smooth the measurement image.The measurement image is segmented based on the histogram of the statistical measurement image,and the target features of the measurement image are extracted using neural network algorithms to achieve automatic detection of targets in coal mine geological unmanned aerial vehicle aerial photography measurement images.Through case application analysis,it can be seen that the recall rate of this design method is over 97%,and the false detection rate does not exceed 1%,indicating that the detection accuracy of coal mine geological unmanned aerial vehicle aerial photogrammetry image targets is high.
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