Algorithm for segmentation of insect pest images from wheat leaves based on machine vision

Automatic inspection is one of the research directions of precision agriculture. Taking the example of Aphid, the authors studied the algorithms for automatically classifying and segmenting insect pest images in non-specific environment respectively based on machine vision. For classification, a Support Vector Machine (SVM) sorter was trained and the method of k-means clustering algorithm was developed. Compared with SVM sorter, k-means has its superiority in rate and SVM has superiority in precision. For segmentation, region-growing algorithm which combined merge and fission was applied to segment the images of insect pest and wheat leaves. The analysis indicate that effect of classification is good and recognition accuracy is 90.7%, the speed can meet the requirement of real-time image processing. These algorithms provided the technology support for precision spraying in agricultural mechanization.