Identification of pests hidden in wheat kernels based on support vector machine classifier

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. RÉSUMÉ. L'identification des parasites cachés dans les blés stockés, essentielle à la sécurité du stockage du grain, est une difficulté majeure dans la recherche sur la détection des cibles. Cet article présente le classifieur de machine à vecteurs de support (en anglais support vector machine, SVM) pour identifier les parasites cachés dans les noyaux de blé et sélectionne la fonction et les paramètres du noyau appropriés pour classifier divers échantillons. Il est vérifié que la méthode proposée pourrait détecter avec précision les parasites dans les noyaux de blé. Cette recherche fournit de nouvelles perspectives sur l'application de la reconnaissance de formes à la détection par bio-photon des parasites cacshés dans les grains stockés.

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