A Macro-distance Video Image Recognition Method for Soil Evolution

Abstract

The invention discloses a method for identifying the microspur video image of soil evolution. The method comprises the following steps: establishing a microspur video grey scale image database, establishing a corresponding relation between every substance and the grey level interval in the database, carrying out statistics on the relation between the quantity of pixels in the grey level interval, representing all substances, and the content or form of the substances in the microspur video grey scale image, and determining the practical characteristic parameters of soil to be detected according to the relation in order to determine the growth of the soil. The method allows onsite microspur video assessment of a soil sample to be directly carried out without a process from onsite soil disturbance sampling to laboratory test, so the test precision is improved; the composition components and the evolution identification of the soil are accurate; and soil in a region can be continuously monitored in real time for a long term through the microspur video image monitoring and assessing method of the soil evolution in order to obtain the evolution rule of the soil in the region.

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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