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For the problems of poor real-time of rice planthopper recognition and a certain error of BP neural network classifier, a rice planthopper recognition system was designed based on DSP hardware system and genetic algorithm optimized BP neural network. AT89S52 microcontroller was used to control the mobile device. DM6437 was used as processing platform. Mathematical morphology algorithm, improved Hu moment, and genetic algorithm optimized BP neural network algorithm were used for segmentation. The video camera was used to shoot crop video. Then, the video signal images were transformed to the DSP recognition system. The rice planthopper could be identified from these images. The experiment was carried out on 80 samples, including rice planthopper, ephydrid and miner. Results showed that the accuracy of genetic algorithm optimized BP neural network reached to 90%.