Tea picking method based on image and point cloud data processing

Abstract

The invention discloses a tea leaf picking method based on image and point cloud data processing, and relates to the technical field of tea leaf picking. The invention discloses a tea picking method based on image and point cloud data processing, and the method comprises the following steps: carrying out the shooting of a thermal image of a cutting knife and a tea tree crown through a thermal imager, carrying out the scanning of a laser radar, obtaining the point cloud information of the cutting knife and the tea tree crown, and selecting a region of interest S according to the thermal image, calculating to obtain the number n of tender shoots in the region of interest S; fitting to obtain a curve of the tea tree crown, and calculating to obtain a distance d2 between the cutting knife and the tea tree crown; and judging according to n and d2, then adjusting the position of the cutting knife, and finally cutting. The invention discloses a tea picking method based on image and point cloud data processing, and the method comprises the steps: processing the crown information of a tea tree through a thermal imager and a laser radar, and adjusting the relative position between a cutting knife and the crown of the tea tree, thereby effectively improving the tea picking precision.

Description

technical field [0001] The invention relates to the technical field of tea picking, in particular to a tea picking method based on image and point cloud data processing. Background technique [0002] my country is a veritable big country in tea planting and production. In 2020, the output and output value of dry raw tea in the country will reach 2.986 million tons and 262.658 billion yuan respectively. Mainly, it is a labor-intensive industry. From the perspective of tea picking, on the one hand, the high cost of manpower picking increases the production cost of tea; on the other hand, due to the short time of tea picking and the low efficiency of manpower picking, the output of tea is severely limited. At present, the contradiction between tea picking and labor in my country has become a bottleneck in the development of the tea industry, so many scientific and technological personnel have begun to study automatic tea picking devices to solve the above problems. [0003] Ex...

AI Technical Summary

Problems solved by technology

[0004] Although the tea picking machine can improve the picking efficiency, it lacks selectivity. When working, it does not distinguish between old and young, and cuts it off with one knife, which makes the buds and leaves of different sizes and poor integrity. It also causes great mechanical damage to the tea tree. Mixed old and tender leaves, old stalks, old leaves and damaged leaves have a high content, which affects the promotion and use of tea picking machines to a certain extent. Automated and intelligent tea picking machinery is an urgent need for the tea industry. In order to improve the integrity and Consistency, improve the overall quality of tea, developed the use of image recognition to select the young buds and then pick them. However, due to the overlapping of old leaves and young leaves of tea trees, the color difference of tea leaves is small, and the method of image recognition alone still cannot solve the picking accuracy. The problem

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