Insect Identification and Counting in Stored Grain: Image Processing Approach and Application Embedded in Smartphones

Abstract

Insects can cause a major loss in stored grain, and early identification and monitoring of insects become necessary for applying corrective action. Considering the effectiveness and practicability, an image processing approach and the corresponding application embedded in smartphones are proposed to identify and count the insects. For the insect images acquired by mobile phones, one sliding window-based binarization is adopted to release their nonuniform brightness, and then connected domain-based histogram statistics is presented to identify and count the insects in stored grain. Finally, the experiments are performed on the corresponding application based on Android, and it has shown that the proposed approach can be applicable for different random insect images from mobile phones with the counting accuracy of 95%, which is superior to the traditional approach.