Identification method for distinguishing locust species by using image identification technology

Abstract

The invention provides an identification method for distinguishing locust species by using an image identification technology. Different biological characteristic identification methods of various locusts, such as the appearance characteristics, body length and the like of the wing feet, are summarized; an image recognition algorithm engineer can train the recognition model according to the distinguishing method; the locust types, such as Asian locust, migratory locust, locust crumpled with knees, rice locust and other common types, are automatically judged and recognized from the shot locustimages, so that the occurrence types and occurrence density of different locusts are monitored, the locust damage monitoring work requirements are effectively met, and locust damage is more effectively prevented and controlled. The method can accurately and efficiently distinguish the locusts of different types, has the characteristics of high efficiency, simplicity, convenience, automation, strong specificity, high accuracy, high stability and the like, and can save a large amount of manpower and material resource costs.

Description

technical field [0001] The invention relates to locust biology research technology in the field of plant protection. Background technique [0002] Locusts are the most serious pests that damage crops in the history of our country. At present, image recognition technology can automatically monitor the occurrence density of locusts in the field to judge the occurrence of locusts, but it is still not possible to accurately identify the species of locusts to monitor the occurrence of locusts. What are the types and the occurrence density of different types of locusts, and currently in the work of locust plant protection, the ability to accurately determine the type of locust infestation is the focus and point of actual locust infestation monitoring, so that the current situation and development trend of locust infestation can be accurately located, and for Take preventive measures in a timely manner to provide more accurate information and opportunities. Contents of the invent...

AI Technical Summary

Problems solved by technology

[0002] Locusts are the most serious pests that damage crops in the history of our country. At present, image recognition technology can automatically monitor the occurrence density of locusts in the field to judge the occurrence of locusts, but it is still not possible to accurately identify the species of locusts to monitor the occurrence of locusts. What are the types and the occurrence density of different types of locusts, and currently in the work of locust plant protection, the ability to accurately determine the type of locust infestation is the focus and point of actual locust infestation monitoring, so that the current situation and development trend of locust infestation can be accurately located, and for Make timely prevention and control measures to provide more accurate information and opportunities

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