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Tự động nhận dạng một số loại sâu bệnh trên lá bưởi sử dụng công nghệ ảnh

2017; Volume: Công nghệ TT 2017; Linguagem: Inglês

10.22144/ctu.jsi.2017.012

2815-5599

Nguyễn Minh Triết, Trương Quốc Bảo, Trương Quốc Định,

Medical Research and Treatments

Nowadays, information technology is widely applied in agriculture - the most developed field in Viet Nam. Among these applications, the detection and recognition of pests system using handle image technique and computer vision have been attracted by many researchers. In this paper, the detection and recognition pests are resolved through two main phases: (1) detect possible areas that are pests; (2) identify the pests from the possible areas detected. In the first phase, segment method is used to detect possible areas. Binary segment and contour detection method is used to get and hightlight related objects in this phase. In the second phase, some colour features and shape features are extracted from images. Then, combined with extracted features, support vector machines are built to classify the image areas which are found in the previous phase. Classification models are trained to recognize four grapefruit leaf pests. The training results are over 99.5% for each model. The experimental result over 500 images is 99.2%. These results show that the proposed method achieves promising results and can be applied to identify the pests in reality.