Research on Image Acquisition and Recognition for Stored Grain Pests

Manual ways of recognizing stored grain pests which are trapped is very time-consuming. In this study, an image dataset of 9 species of pests was built up by finding the MSERs (Maximally Stable Extremal Regions), through a trap of stored grain pests combined with a real-time imaging device. On this basis, the localization and recognition of stored grain pests were achieved. The experimental results on 3600 images showed that by the combination of shape features and color features, the average F1 score was about 0.947 by selecting the appropriate parameters of SVM (Support Vector Machines) classifier. Keywordsstored grain pests; image dataset; MSERs; color features; shape features