Abstract: Insects in the wetlands of Erhai Lake are small and difficult to identify. In order to improve the efficiency of intelligent
insect data processing and classification, an intelligent insect identification method was designed for the Erhai Lake wetland insects.
The method realizes insect image classification learning through SVM-AdaBoost machine learning model. Based on IOS mobile
platform, this paper adopts MVC（Model View Controller）design pattern and uses Swift language to realize the functions of insect
image acquisition, display, recognition and so on. The real-time performance test shows that the method has good reliability and meets
the real-time requirement of intelligence. Through the evaluation of insect image recognition, the result shows that the algorithm can
recognizewetlandmicro-insectsintelligently.Itsrecognitionaccuracyandcallbackratereached 92%,andtheaccuracyratereached 91%.

Key words: insect image processing, intelligent classification and recognition, support vector machine, AdaBoost algorithm, accuracy