A monitoring method of Mikania micrantha based on image recognition
An image recognition and Mikania micrantha technology, applied in the field of Mikania micrantha monitoring based on image recognition, can solve the problems of low monitoring efficiency of Mikania micrantha outbreaks, and achieve the effects of accurately judging the degree of harm, strong resistance to variation, and high computing efficiency
Active Publication Date: 2022-08-09
GUANGXI UNIV
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[0004] The purpose of the present invention is to provide a method for monitoring Mikania micrantha based on image recognition, which overcomes the existing shortcomings of low monitoring efficiency for the outbreak point of Mikania micrantha in full bloom
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[0028] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings, but it should be understood that the protection scope of the present invention is not limited by the specific embodiments.
[0029] Unless expressly stated otherwise, throughout the specification and claims, the term "comprising" or its conjugations such as "comprising" or "comprising" and the like will be understood to include the stated elements or components, and Other elements or other components are not excluded.
[0030] like Figure 1-3 As shown, a method for monitoring Mikania micrantha based on image recognition, comprising the following steps:
[0031] In step S1, the camera 2 carried by the UAV 3 is used to photograph the area to be monitored at equal intervals to obtain a plurality of aerial photographs of Mikania micrantha, and the aerial photograph of Mikania micrantha is transmitted to the computer 4;
[0032] Step S2, constru...
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The invention discloses a method for monitoring Mikania micrantha based on image recognition, which belongs to the technical field of image intelligent recognition. The method includes the following steps: photographing the area to be monitored by the camera carried by the drone at equal intervals, obtaining multiple aerial photographs of Mikania micrantha, and transmitting the aerial photographing images of Mikania micrantha to a computer; constructing a threshold segmentation algorithm, debugging the aerial images of Mikania micrantha in the sampling set as described in the description The average parameter and standard deviation parameter of the threshold segmentation algorithm are used to calibrate the threshold segmentation algorithm used to identify Mikania; the Mikania aerial image is processed by the image synthesis algorithm, and then transmitted to the threshold segmentation algorithm, and then processed by the image enhancement algorithm. A binary image of the identification information of Mikania; according to the UAV flight height parameter and the camera wide-angle parameter, combined with the binary image, the Mikania distribution map and the Mikania distribution area are obtained. The present invention overcomes the existing shortcomings of low monitoring efficiency for the outbreak point of Mikania micrantha in full bloom.
Description
technical field [0001] The invention belongs to the technical field of image intelligent recognition, in particular to a method for monitoring Mikania micrantha based on image recognition. Background technique [0002] Mikania micrantha, a genus of Asteraceae, is native to America and is a highly harmful invasive weed. In the early 1980s, Mikania micrantha was discovered to be introduced into South China, endangering local vegetation and agricultural and forestry crops and causing huge economic losses. [0003] At present, there are few studies on automatic identification of Mikania micrantha. There are related studies based on satellite remote sensing technology, hyperspectral remote sensing technology, and deep learning technology, but they all have great limitations. Therefore, with the increasing severity of Mikania hazard and the shortcomings of existing monitoring methods, there is an urgent need to develop a high-precision monitoring method to quickly, accurately and...
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IPC IPC(8): G06V20/17G06V20/10G06V10/26G06V10/20G06T7/62G06T7/11G06T7/136G06T5/30G06T3/40
CPCG06T7/62G06T7/136G06T7/11G06T5/30G06T2207/30188G06T2207/10032G06T2207/30232G06V20/188G06V10/20G06V10/267
Inventor 李岩舟范卿麦聪施瑞吴舒晗林涛田洪坤刘亚东王天海江欣
Owner GUANGXI UNIV