Pine wood nematode disease epidemic wood recognition and positioning method based on an unmanned aerial vehicle aerial photograph original film

Abstract

The invention relates to the technical field of pine wood nematode disease image recognition and positioning, and discloses a pine wood nematode disease epidemic wood recognition and positioning method based on an unmanned aerial vehicle aerial photograph original film, after an epidemic wood is recognized on an original film, a self-designed special mark is embedded in the position of the epidemic wood, the special mark has obvious appearance characteristics in a mountain forest, the orthographic image is not easy to be confused with other objects, and the characteristics of the orthographic image can still be kept after the orthographic image is spliced; and the special marks are detected and identified on the orthoimage with precise latitude and longitude information, and the latitude and longitude position of each special mark can be accurately obtained, so that the number and distribution of the epidemic wood in the target mountain forest area range can be accurately counted, and precise identification and positioning of the pine wood nematode disease epidemic wood can be realized.

Description

technical field [0001] The invention relates to the technical field of image recognition and positioning of pine wood nematode disease, specifically, a method for recognition and positioning of pine wood nematode disease-infested trees based on the original aerial photograph of a drone. Background technique [0002] Pine wood nematode disease, also known as pine wilt disease, is a devastating forest disease caused by pine wood nematode. After being infected by pine wood nematode, the needle leaves are yellowish brown or reddish brown, wilting and drooping, resin secretion stops, and gradually Dry and die, and eventually rot. Due to the strong pathogenicity of pine xylophilus, the host dies quickly, spreads quickly, and the forest area is large, so it is difficult to detect in time and control is difficult. [0003] Because the infected pine wood nematodes are yellowish-brown or reddish-brown, and the needles gradually wither, they are different from normal pine trees and oth...

AI Technical Summary

Problems solved by technology

[0006] However, the disadvantage of the technical scheme of identifying the diseased wood directly on the original aerial film of the UAV: ​​when the UAV collects the mountain forest image, although the single original film taken by the UAV can also obtain the information obtained by the UAV when the original film was taken according to the GPS signal. However, due to the influence of the UAV flight angle and route planning and the wind direction at that time, the longitude and latitude coordinates cannot be accurately located at the exact center of the image. At the same time, due to the undulating terrain of the mountains and forests, it is impossible to accurately locate the image in the original film. It is difficult to accurately locate the identified diseased tree in latitude and longitude, and the same plant of diseased tree in the adjacent original film cannot be accurately matched and deduplicated. Therefore, although the identification effect of the diseased tree is better, but It is impossible to accurately count the number and distribution of the diseased trees in the region

[0008] However, the shortcomings of the identification and positioning technology scheme on the spliced ​​orthophoto images: in the process of matching and splicing the original drone aerial photos, due to the different shooting positions of the adjacent original photos, the existence of viewing angle distortion, the matching is not accurate enough, Due to the shaking of leaves caused by the external wind direction, the spliced ​​orthophoto images have ghosting, blurring, etc., and the image quality has declined to a certain extent compared with the original film taken by the drone. Precise latitude and longitude positioning for each pixel position, but it has a greater impact on the recognition accuracy of the diseased wood

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