Model and Algorithm for the Detection of Hidden Insects in Wheat

Abstract:

In order to prevent the loss of grain mass and quality，a fast and efficient method for the early detection of insects in grains is urgently needed during trade and storage. Based on the biophoton analytical technology（BPAT），the experiments were made to measure spontaneous photon counts of wheat kernels and infested ones. Then statistical characteristics and histogram distribution were extracted and linear discriminant analysis（LDA） and quadratic discriminant analysis（QDA） were used to discriminate between normal and infested grains. In addition，due to the singularity and instability of the per class covariance matrices in the small sample，regularized discriminant analysis（RDA） was used to optimize QDA and increase the classification accuracy. Therefore，the proposed method is workable.