Find in Library

<b>Objective:</b> Improve the speed and accuracy of foreign matter identification in food. <b>Methods:</b> Based on the LeNet-5 network structure, the improved CNN model was obtained by adding batch normalization layer and dropout layer. Using this model, a recognition system was established for the automatic recognition of foreign bodies in food images. The performance of the model was analyzed through experiments. <b>Results:</b> Compared with the traditional model, this model has higher detection accuracy and faster recognition speed. The recognition accuracy of food foreign bodies was 99.75% and the recognition time was only 0.332 s. <b>Conclusion:</b> The foreign object recognition model of dumpling image had good detection speed and recognition accuracy.