Image Recognition and Classification of the Stored-grain Pests Based on Support Vector Machine

Abstract

The image recognition of the stored-grain pests is few-sample, multi-feature and multi-compound degree of various pests. The design of the classifier is a very important part for the stored-grain pests’ detection system. The grid search was proposed to optimize parameters and in the classifier based on support vector machine, by the judgment rule that is the recognition ratio of the cross-valid train model. The nine categories of the stored-grain pests in grain-depot were automatically recognized by the classifier based on support vector machine, the correct identification ratio was over 93%. The experiment showed that it was practical and feasible.