A Macro-distance Video Image Recognition Method for Soil Evolution

Abstract

The invention discloses a macro video image recognition method of soil evolution. First, a macro video grayscale image database is established. Then, the corresponding relationship between each substance and the grayscale value interval is established in the database. Then, macro statistics are The relationship between the number of pixels in the gray value interval of each substance in the video grayscale image and the substance content or form is determined. Finally, based on the above relationship, the actual characteristic parameters of the soil to be detected are determined, and then the development status of the soil is determined. This invention does not need to go through the process of on-site soil disturbance sampling to laboratory testing, but directly conducts macro video evaluation of on-site soil samples to improve test accuracy; more accurately identify soil components and their evolution; the soil evolution The macro video image monitoring and evaluation method can conduct long-term continuous real-time monitoring of the soil in a certain area, thereby obtaining the evolution rules of the soil in the area.

Description

technical field [0001] The invention relates to the field of soil evolution monitoring, in particular to a macro video image recognition method for soil evolution. Background technique [0002] At present, the detection and evaluation of soil performance mainly adopts the field test method mainly based on manual measurement. In this method, the traditional manual measurement requires on-site sampling first, which greatly disturbs the soil. The soil samples obtained in this process The performance has deviated from the state of real soil particles, so its accuracy is far from enough; secondly, the obtained soil samples are often returned to the laboratory for testing and analysis, and the efficiency is extremely low; and in this process, the temperature, moisture and distribution of the soil samples, Various parameters such as the degree of combination of soil particles and moisture are easily changed due to soil sample preservation and manual operation. Obviously, the accura...

AI Technical Summary

Problems solved by technology

[0002] At present, the detection and evaluation of soil performance mainly adopts the field test method mainly based on manual measurement. In this method, the traditional manual measurement requires on-site sampling first, which greatly disturbs the soil. The soil samples obtained in this process The performance has deviated from the state of real soil particles, so its accuracy is far from enough; secondly, the obtained soil samples are often returned to the laboratory for testing and analysis, and the efficiency is extremely low; and in this process, the temperature, moisture and distribution of the soil samples, Various parameters such as the degree of combination of soil particles and moisture are easily changed due to soil sample preservation and manual operation. Obviously, the accuracy of the test results is not enough

Each test result can only represent the state of the soil at that time, and cannot accurately express the evolution process of the soil

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