The identification of pests hidden in stored wheats, essential to grain storage safety, is a key difficulty in the research of target detection. This paper introduces the support vector machine (SVM) classifier to identify the pests hidden in wheat kernels, and selects the proper kernel function and parameters to classify various samples. It is verified that the proposed method could accurately detect the pests in wheat kernels. This research provides new insights into the application of pattern recognition in bio-photon detection of pests in stored grains.
grain kernels, support vector machine, classification, characteristic parameter
The authors acknowledge the National key research and development project (No: 2017YFD0401004, No: 2017YFD0401003), Doctoral Fund of Henan University of Technology (Grant: 2017BS034); Food information processing and control laboratory of the key laboratory of ministry of education (Grant: KFJJ-2016-103), National Science Foundation of China (61741107), Key projects of Henan science and Technology Department (172102210230).
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