Method for identifying microspur video image of soil evolution

A technology of video image and identification method, applied in the field of soil evolution monitoring, can solve the problems of inability to accurately express the soil evolution process, insufficient accuracy of test results, large soil disturbance, etc., achieve rapid real-time data analysis technology, improve testing Efficiency, Evolution Identify Precise Effects

Inactive Publication Date: 2016-11-09
WUHAN UNIV
9 Cites 7 Cited by

AI-Extracted 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 testin...
View more

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.

Application Domain

Image enhancementImage analysis +3

Technology Topic

Image databaseAssessment methods +9

Image

  • Method for identifying microspur video image of soil evolution

Examples

  • Experimental program(1)

Example Embodiment

[0029] In order to facilitate the understanding and implementation of the present invention by those of ordinary skill in the art, the present invention will be further described in detail with reference to the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.
[0030] With the rapid development of information technology, macro video image processing technology has provided a technical means that was not available in the past for the development of modern science and technology, and has been widely used in many disciplines. At the same time, it also provides a feasible way for the monitoring and evaluation of soil evolution process, and provides faster real-time data analysis technology for predicting the evolution of soil properties.
[0031] In the process of soil development, soil particle size, moisture content and porosity will all change. In the natural environment, the physical and chemical changes of the soil itself change the parameters of the soil. If the temperature is low, part of the water in the soil will freeze into ice, that is, there will be ice particles in the soil. These changes will eventually lead to the evolution of soil properties. There may be rocks and other impurities in the soil. Because soil particles, voids, moisture, ice and other substances absorb or reflect light differently, the macro video images taken by these substances in the soil are converted into macro After the video gray image, it will show different gray values. Therefore, different substances can be identified by analyzing different gray values ​​of soil macro video images.
[0032] Please see figure 1 , The invention provides a soil evolution macro video image recognition method, including the following steps:
[0033] Step 1: Under the condition of self-installed light source, use macro video image acquisition equipment to photograph and image the soil in different development states. Then, the original true color macro video image is converted into a macro video gray image, and a macro video gray image database is established.
[0034] Among them, the lens of the macro video image acquisition device can be replaced with a lens with different magnifications as needed; soils with different development states are soils with different sizes of soil particle size, porosity, water content and ice content.
[0035] Step 2: Because the grayscale images of different substances (soil particles, pores, moisture, ice and other substances) have different grayscale value intervals, establish a one-to-one correspondence between substances and grayscale value intervals in the database, that is, Different substances in the grayscale image of the macro video are encoded.
[0036] Step 3: Including the following sub-steps;
[0037] (1) Count the number of pixels in the gray value interval representing moisture in the macro video grayscale image and the gray average value of the pixels in the gray value interval representing soil particles, and then establish them and the soil moisture Rate of quantitative relationship;
[0038] (2) Count the number of pixels in the grayscale value interval representing ice in the macro video grayscale image, and then establish a quantitative relationship between it and the ice content of the soil;
[0039] (3) Count the number of pixels in the gray value interval representing the pores in the macro video gray image, and then establish the quantitative relationship between it and the porosity of the soil.
[0040] Step 4: Binarize the macro video grayscale image, and then perform bridging, de-mixing, thinning and ossification processing to obtain the contour of the soil particles. Then, count the number of pixels in each soil particle, and finally establish a quantitative relationship between the average number of pixels and the average particle size of the soil particles.
[0041] Among them, the binarization macro video grayscale image regards soil particles and other substances as one kind of substance, and then performs binarization to determine the outline of the soil particles; bridging and de-cluttering are handled by opening and closing operations Remove the isolated noise points in the macro video image, while retaining the original detailed structure in the macro video image; the macro video image refinement process is to transform the macro video image into a thin line composed of a single pixel thickness. The video image ossification process is to retain the refinement of the center line of the macro video image.
[0042] Retaining the refinement of the center line of the macro video image, the specific implementation steps are as follows: (1) Do the corrosion operation, but do not delete the pixels immediately, only mark; (2) Delete the mark points that do not damage the connectivity; (3) ) Repeat the execution until the image result does not change, and the refined result is obtained.
[0043] Step 5: Include the following sub-steps;
[0044] (1) Input the original true-color macro video image of the soil to be monitored (taken under the condition of its own light source), and then convert it into a macro video grayscale image, and use step 2 to identify each substance (soil particles) , Pores, moisture, ice and other substances);
[0045] (2) Count the number of pixels in the gray value interval representing moisture and the average gray value of the pixels in the gray value interval representing soil particles in the grayscale image of macro video, and then use step 3 (1) The relationship established in, the moisture content of the soil can be obtained;
[0046] (3) Count the number of pixels in the grayscale value interval representing ice in the macro video grayscale image, and then use the relationship established in step 3 (2) to obtain the ice content of the soil;
[0047] (4) Count the number of pixels in the gray value interval representing pores in the macro video gray image, and then use the relationship established in step 3 (3) to obtain the porosity of the soil;
[0048] (5) Use the method in step 4 to process the macro video grayscale image to obtain the contour of the soil particles. Then, calculate the average number of pixels in each soil particle, and then use the relationship established in step 4 to obtain the average particle size of the soil particles.
[0049] Step 6: Determine the development state of the soil according to the actual characteristic parameters of the soil (including the particle size of the soil particles, the porosity of the soil, the water content and the ice content).
[0050] The invention can quickly identify various parameters of the soil to be monitored, thereby determining the evolution state and degree of the soil to be monitored. Compared with the traditional manual measurement, the traditional manual measurement requires on-site sampling first, which disturbs the soil mass. The performance of the soil sample obtained in this process has deviated from the real soil particle state, so its accuracy is far from enough; 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 soil sample temperature, moisture and its distribution, the degree of soil particle and moisture binding and other parameters are easily affected by the soil. Sample preservation and manual operation have changed, and obviously the test results are not accurate enough. Each test result can only represent the state of the soil at that time, and cannot accurately express and evaluate the evolution process of the soil.
[0051] It should be understood that the parts not elaborated in this specification belong to the prior art.
[0052] It should be understood that the above description of the preferred embodiments is more detailed and should not be considered as a limitation to the scope of protection of the patent of the present invention. Those of ordinary skill in the art, under the enlightenment of the present invention, do not depart from the claims of the present invention. In the case of the scope of protection, alternatives or modifications may be made, and all fall within the scope of protection of the present invention. The scope of protection of the present invention shall be subject to the appended claims.

PUM

no PUM

Description & Claims & Application Information

We can also present the details of the Description, Claims and Application information to help users get a comprehensive understanding of the technical details of the patent, such as background art, summary of invention, brief description of drawings, description of embodiments, and other original content. On the other hand, users can also determine the specific scope of protection of the technology through the list of claims; as well as understand the changes in the life cycle of the technology with the presentation of the patent timeline. Login to view more.

Similar technology patents

Electromagnetic wave cell based on array antennas

ActiveCN106850086AImprove test accuracyStructural rules
Owner:SHENZHEN TOJOIN COMM TECH

Testing device and testing method for temperature sensor consistency

Owner:SHANGHAI INST OF OPTICS & FINE MECHANICS CHINESE ACAD OF SCI

Optical detection system for carbon monoxide concentration

InactiveCN105388125AImprove test accuracydetection limit width
Owner:U COM TELECOM EQUIP CO LTD

Classification and recommendation of technical efficacy words

  • Improve test accuracy

Testing system for mobile terminal and testing method thereof

Owner:广东每通测控科技股份有限公司

Fluid structure interaction coal rock shear-seepage test device

ActiveCN103743633AImprove test accuracyFacilitate data collection and accurate calculation
Owner:CHONGQING UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products