Method for identifying animal and plant pests in multi-dimensional form by applying laser technology

Abstract

According to the invention, a laser technology is adopted to carry out distance measurement on a biological form to generate initial multi-dimensional animal and plant harmful biological form contourpoint cloud data; the method comprises steps of 'denoising' the initial multi-dimensional animal and plant harmful organism form contour point cloud data; reconstructing accurate multi-dimensional animal and plant harmful organism form contour point cloud data, and splitting the accurate multi-dimensional animal and plant harmful organism form contour point cloud data to obtain local form featurepoint cloud data for distinguishing animal and plant harmful organisms based on a harmful organism retrieval table; comparing with a corresponding morphological characteristic standard point cloud database in a pre-trained pest retrieval table, and performing classified retrieval to determine animal and plant pest species. According to the method, the multi-dimensional forming time of the biological sample is greatly shortened, and the Fresnel adding efficiency is improved; and moreover, the method has a memory capability, and the higher the use frequency is, the higher the identification speed is, and the higher the accuracy is.

Description

technical field [0001] The invention belongs to the field of biometric identification of artificial intelligence, and in particular relates to a method for identifying harmful organisms of animals and plants using laser technology in multi-dimensional forms. Background technique [0002] The development of information technology such as the Internet of Things, blockchain, cloud computing, and big data has opened up many application fields for artificial intelligence, and has also put forward higher and higher requirements. Biometric identification is an extremely important part of artificial intelligence. Identification of animal and plant pests (pests, weeds, molluscs, spiders, fungi, nematodes, prokaryotes) is an extremely important application field of biometric recognition. Accuracy, speed, convenience and other issues have put forward high requirements for the intelligent identification method of animal and plant pests. At present, the method of intelligent identificat...

AI Technical Summary

Problems solved by technology

Although this technology can achieve scanning imaging, has the characteristics of digitization and remoteness, it has been tried in the field of animal and plant pest identification, but due to the existence of a single biological sample in the Darmstadt scanning image identification method, 25,000 shots in 400 different spatial directions are required. A photo, the whole process requires precise positioning, multiple placements, and multiple shootings. It took several hours to complete, and the amount of data was very large. As a result, Darmstadt scan biometrics is still only in the experimental stage at present, and it is difficult to enter the application.

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