Quantitative Detection Method of Grain Storage Height in Grain Silos Based on U-Net
Due to the distribution of grain storage in China is characterized by many points,long lines and wide areas,the traditional method of monitoring grain quantity is struggling with low efficiency,high costs,and significant delays.There is an urgent need to research and develop a new technology that can perform real-time and rapid detection of the quantity of grain stored in grain silos.To address the problem,we proposed a quantitative detection method of grain storage height in grain silos based on U-Net.By segmenting the grain surface and ventilation windows in pictures captured by monitoring cameras in the grain warehouse,we obtained pixel values of the edge of the grain surface and the upper and lower edges of the ventilation window.Taking into account the height of the ventilation window's upper and lower edges above and below the ground,we could determine the actual height of grain storage in the grain silo.Subsequently,merged with the length,width,grain density,and other fundamental data,we obtained the actual quantity of grain stored in the grain silo.In this study,the height of grain storage was calculated by analyzing and processing the segmented soil images using U-Net,DeepLabV3+,and PSPNet algorithms respectively.The experimental results showed that the mean intersection over union(MIoU)reached 93.25％,which was 1.82 and 2.69 percentage points higher than that of DeepLabV3+and PSPNet,respectively.The mean pixel accuracy(MPA)reached 95.88％,which was 2.42 percentage points higher compared with PSPNet.The quantitative analysis error of U-Net was 3.51％,which was 1.34 and 0.43 percentage points lower compared with DeepLabV3+and PSPNet,respectively.U-Net was more suitable as a segmentation algorithm for quantitative calculation of grain storage height in granaries.It is not necessary to set up the measuring scale beforehand and with this method.By relying solely on the monitoring camera inside the warehouse,the height measurement of grain pile can be achieved,which can effectively meet the fast detection requirements for the quantity of grain stored in the warehouse.
Quantity of grain stored in granariesGrain storage heightSemantic segmentationU-NetQuantitative analysisComputer vision
万方数据
维普
