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Analysis of the process of reel harvesting lodging crops based on intelligent image processing

ABSTRACT In order to improve the harvesting efficiency of lodging crops, starting from the reel system, this paper combines intelligent image processing algorithms to identify the characteristics of lodging crops. Moreover, this paper optimises the data set, chooses L2 norm regularisation to reduce overfitting, uses exponential decay method to set learning rate, uses moving average model to speed up training convergence speed, improves classification accuracy, and simplifies the structure of the neural network to improve the real-time image recognition effect. A moving average is a statistical estimation that is used to evaluate sets of data by comparing the amounts of various subsets of the entire data set. Simultaneously, this paper improves the traditional reel structure and adds image recognition equipment to recognise crop lodging in real time during harvesting. In addition, this paper reasonably controls the reel system for harvesting, sets the reel working status by identifying lodging crops, and combines image technology to achieve efficient operation of the reel system. Finally, this paper designs experiments to verify the system performance. The research results show that the performance of the system constructed in this paper is good.