Crop-Weed Identification and Location Method Based on 3D Time-of-Flight Imaging

Abstract

Provided is a crop-weed identification and positioning method based on three-dimensional flight time method imaging. When plant seedling stalk characteristics are obvious, a three-dimensional flight time camera is adopted to obtain side view three-dimensional images of plant seedlings; and when plant seedling leaf blade characteristics are obvious, the three-dimensional flight time camera is adopted to obtain overlook three-dimensional images of the plant seedlings. Then three-dimensional soil partition pretreatment is respectively performed on the side view three-dimensional images and the overlook three-dimensional images, a Hough conversion algorithm and a tube characteristic measuring algorithm are adopted to extract stalk characteristics for the plant seedlings with the obvious stalk characteristics; for the plant seedlings with the obvious leaves, a three-dimensional image local area increase algorithm or a continuous method for inspecting local surface normal direction changes is adopted to extract leaf blade proceeding characteristics; weeds are identified and positioned on the basis of characteristic extraction, and rapid and automatic weeding operation can be performed by matching with a weeding device; simultaneously plant stalk and seedling center positions undergo three-dimensional reconstruction and positioning, accurate positioning of the crop plant seedlings is performed, crop growth data such as planting distances and seeding numbers of crops are obtained automatically, and dynamic automatic accurate management of crop growth is facilitated.

Description

technical field [0001] The invention relates to a crop-weed identification and positioning method based on three-dimensional time-of-flight imaging. technical background [0002] my country is a large agricultural country, and there are many kinds of weeds in the farmland with a wide distribution range. In traditional agriculture, the infestation of weeds is one of the main problems that plague the growth of crops. [0003] According to the statistics of the National Plant Protection Center of the Ministry of Agriculture, the amount of labor spent on weeding in my country is as high as 2-3 billion labor days every year, and the labor for weeding in farmland accounts for 1 / 3-1 / 2 of the total field workload. The grain loss caused by weed disasters in my country still reaches an average of 13.4%, and the annual loss of grain production is about 17,500 thousand tons. In recent years, with the development of the country's economic production, the number of people engaged in agr...

AI Technical Summary

Problems solved by technology

However, the existing image pattern recognition is based on two-dimensional image processing, and it is difficult to identify and locate when the leaves of crops and weeds overlap and block

Its recognition rate is low and its positioning is inaccurate

At the same time, at present, the observation and measurement of crop growth status, plant spacing and seedling number are mainly carried out manually, which consumes a lot of human resources and the measured data has large errors, which cannot meet the needs of modernization and automation of agricultural production.

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