Method for identifying mildewed peanuts through near-infrared hyperspectral image based on deep learning algorithm

Abstract

The invention discloses a method for identifying mildewed peanuts through near-infrared hyperspectral images based on a deep learning algorithm, and the method comprises the steps: carrying out the near-infrared hyperspectral imaging of to-be-identified peanuts, and obtaining the data of the near-infrared hyperspectral images; constructing a deep belief network (DBN) model for identifying the mildewed peanuts according to different spectral responses of the mildewed peanuts and the healthy peanuts, and generating a peanut mildewing information distribution diagram; judging whether one to-be-identified peanut particle is mildewed or not according to the mildewing pixel number of each peanut particle in the mildewing information distribution diagram and a threshold value (beta), and generating a mildewed peanut identification result diagram; the method can efficiently and accurately identify the mildewed peanuts, is high in identification precision, and is beneficial to improving the quality of oil extracted from the peanuts and corresponding food.

Description

technical field [0001] The invention relates to a method for identifying moldy peanuts, in particular to a method for identifying moldy peanuts based on a near-infrared hyperspectral image based on a deep learning algorithm. Background technique [0002] Peanut is one of the important sources of edible oil and has rich nutritional value. During the growth and storage of peanuts, mildew is easily caused by improper storage conditions, and moldy peanuts often contain aflatoxin. Aflatoxin can damage the liver of mammals, induce hepatocellular carcinoma, and pose a serious threat to human health. Therefore, there is an urgent need to develop a detection technology that can effectively identify and separate moldy peanuts before peanuts enter the production process, so as to prevent aflatoxin from entering the food chain. In this way, it helps to reduce the content of aflatoxin in peanuts and their products, which can improve food safety and is of great significance to human hea...

AI Technical Summary

Problems solved by technology

However, at present, deep learning research on the hyperspectral recognition of moldy peanuts is lacking. Therefore, it is necessary to explore the construction of a hyperspectral image recognition model for moldy peanuts based on deep learning, so as to improve the accuracy of peanut moldy information acquisition, thereby improving the quality of moldy peanuts. recognition accuracy

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