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In order to improve the large-scale production efficiency of corn and realize the intellectualization and automation of corn seed metering technology, it is necessary to combine modern computer technology with intelligent algorithm to establish a feasible model suitable for corn seed metering device. In this paper, watershed algorithm and EDEM (EM Solutions EDEM) algorithm are used to establish an efficient corn particle recognition model. Watershed algorithm is used for image matching and recognition, EDEM algorithm is used for simulation and processing of corn particles. Twenty corn seeds were selected, and the proportion and volume fraction of seeds with different shapes were calculated by using the model. The parameters needed for simulation were calibrated to verify the reliability of corn sowing accuracy. Through the credibility evaluation of RTM (Resin Transfer Moulding) model in maize seed metering model, it can be seen that the model has credibility, and the variance test result P = 0.662 > 0.10 shows that the credibility of the model meets the requirements. The results show that the model can be applied to the large-scale production of corn seed metering device, greatly improve the production efficiency, has high reliability, and is worthy of practical application and promotion. In this paper, the model construction and Simulation of corn planter based on EDEM are deeply studied and analysed, and the related processes are improved, so as to comprehensively improve the work efficiency of corn planter and improve the quality of planter.