CN202794042U - Device for quickly and preliminarily judging soil type through panoramic annulus photographic method - Google Patents

Abstract

The utility model discloses a device for quickly predicting soil types by using a panoramic annular photography method. The pillar is fixed vertically on the base, one end hole of the two beams is fixed on the pillar, the ring belt camera connecting rod passes through the other end holes of the two beams, the panoramic ring belt camera and the miniature laser rangefinder probe are installed at the lower end, the probe is connected with the laser The host of the range finder is connected, the host of the laser range finder and the transmission system are respectively installed on the upper beam, the gear in the transmission system meshes with the rack on the side of the connecting rod of the ring belt camera and moves in the center hole of the base, and the camera is connected with the computer. Move the device above the soil hole of the soil to be tested, and the stepping motor moves the camera vertically down to the position to be measured in the soil hole, and every time it moves up 5cm, the camera is controlled by the computer to take pictures; the panoramic ring image is expanded into Rectangular image, using the correlation of image texture features to measure the similarity between the expanded image and the standard soil type profile image to quickly predict the soil type.

Description

A device for quickly predicting soil types using panoramic ring photography

technical field

The utility model relates to a device for soil type, in particular to a device for quickly predicting soil type by using a panoramic ring photography method. the

Background technique

Soil refers to the loose layer of the earth's land surface that can produce plant harvests. It is the base of agricultural production and an important part of the natural geographical environment of the earth's surface system. Due to differences in soil-forming factors, different types of soil are distributed on the land surface. Correct soil classification and mapping are the basis for understanding soil, and are also the basis for land evaluation, land use planning, and promotion of agricultural technology according to local conditions. the

Conventional field soil type prediction methods are usually to comprehensively judge by excavating soil profiles, comparing and observing its properties and geological background conditions. Under field working conditions, the natural exposed section can be readily utilized with deep excavation, wide extension and good continuity. However, the manual section excavation process is time-consuming and laborious, and the requirements for the width and depth of the main section are different under different circumstances, and additional inspection sections and a large number of delimiting sections need to be set up. In order to ensure the quality of soil type survey results, a certain number of soil profiles must be set within a certain range, which directly determines that field collection of soil profiles must be a very heavy work. the

The newly developed method of discriminating soil types or characteristics mainly uses digital image processing technology. At present, it mainly uses digital images such as soil slices, CT (computed tomography technology), and SEM (scanning electron microscope) to carry out soil pore fractal characteristics ( He Juan, Liu Jianjian, Lv Fei. Research on fractal characteristics of soil pores based on CT digital images. Soil, 2008, (04):662-666), soil microscopic characteristics (Zhang Rui, Zhang Xiaolong, Tang Hui, Huang Ying. Soil body SEM Image Quantitative Analysis System and Application. Journal of Jiangxi Normal University (Natural Science Edition), 2011, 5(2):165-169.). Li Decheng, Nanjing Institute of Soil Science, Chinese Academy of Sciences, etc. used excavated soil slices and digital image methods to study the variation of soil porosity in the vertical direction of the profile (Li Decheng, VELDE B, DELERUE J F, Zhang Taolin. Using soil slices and digital image methods to study soil porosity Vertical spatial variability. Soil and Environment, 2000, 9(2): 135-138.). However, in these studies, soil slices must first be excavated and sampled, and then undergo secondary treatments such as solidification. The research process is relatively complicated, and the imaging equipment used is expensive and the research period is long. The ring photography method used is based on the 360° viewing angle staring panoramic imaging system, which is obtained by applying the new cylindrical/plane projection imaging principle, and can realize 360° ring space imaging. Its field of view is a hemisphere or even exceeds a hemisphere. The method has broad application prospects in aviation, national defense, medicine, geological exploration and other fields. the

In the above studies, there is no report on the method and device for quickly predicting soil types by using the panoramic ring photography method. the

Contents of the invention

In order to overcome the time-consuming, labor-intensive and long-term defects of the existing soil type discrimination, the purpose of the utility model is to provide a device for quickly predicting the soil type by using the panoramic ring photography method. the

The technical scheme that the utility model adopts is:

There is a central hole on the circular base, the pillars are vertically fixed on the base, fixing screws and adjusting screws are installed under the base and arranged in an equilateral triangle, the glass horizontal bubble is fixed on the base, and one end of the first beam and the second beam The holes are respectively fixed on the pillars from bottom to top. The other ends of the first beam and the second beam are respectively provided with holes. The two holes are coaxial with the central hole of the base. The connecting rod of the ring belt camera passes through the other end of the first beam and the second beam. One end hole, the panoramic ring camera is installed at the lower end of the ring camera connecting rod, the panoramic ring camera is equipped with a downward-facing miniature laser rangefinder probe, and the miniature laser rangefinder probe is connected to the host of the miniature laser rangefinder with display screen through a cable , the upper end of the connecting rod of the belt camera is provided with a groove for installing the extension rod, and the main unit and the transmission system of the miniature laser rangefinder with display screen are installed on the second beam respectively, and the gears in the transmission system are connected with the rack on the side of the connecting rod of the belt camera The connecting rods of the ring-belt camera drive the panoramic ring-belt camera to move up and down in the vertical direction in the center hole of the base, and the panoramic ring-belt camera is connected with the computer through a cable. the

There is a rack on the side of the extension rod, and one end of the extension rod protrudes and is inserted into the groove where the extension rod is installed and locked into one body. the

The transmission system is composed of a stepping motor, a gear mounted on the shaft of the stepping motor and a ratchet and pawl mechanism. the

The beneficial effects that the utility model has are:

The utility model utilizes the panorama ring photography technology to image the cave wall at the same height in a vertical cylindrical soil cave with a small diameter at one time as a panorama ring image, and after the panoramic ring image is unfolded and spliced , by calculating the similarity between the mosaic image and the standard soil type, the soil type can be quickly identified without digging a large soil profile. the

Description of drawings

Fig. 1 is a three-dimensional structure diagram of the present utility model. the

Fig. 2 is a perspective view of the extension rod. the

FIG. 3 is a plan view of FIG. 1 . the

Fig. 4 is a schematic diagram of the expansion of the panorama ring image in the tangential direction. the

Fig. 5 is a schematic diagram of a panoramic ring image. the

Fig. 6 is a top view of the panorama ring image tangentially expanded. the

In the figure: 1. Base, 2. Pillar, 3. First beam, 4. Transmission system, 5. Second beam, 6. Fastening screw, 7. Groove, 8. Adjusting screw, 9. Glass level bubble, 10. Center hole, 11. Panoramic ring belt camera, 12. Miniature laser rangefinder probe, 13. Miniature laser rangefinder host with display screen, 14. Ring belt camera connecting rod, 15. Extension rod, 16. Fixing hole , 17, protrusion, 18, fixing screw. the

Detailed ways

Below in conjunction with accompanying drawing and example the utility model is described further. the

As shown in Figure 1, Figure 2 and Figure 3, a central hole 10 is opened on the circular base 1, and the pillar 2 is vertically fixed on the base 1, and the fixing screw 18 and the adjusting screw 8 are installed under the base 1 and are equilateral triangles. Arrangement, the glass level bubble 10 is fixed on the base 1, the glass level bubble 10 is located in the middle of the line connecting the centers of the two adjusting screws 8, and the end holes of the first beam 3 and the second beam 5 are respectively fixed on the pillar 2 from bottom to top The other ends of the first crossbeam 3 and the second crossbeam 5 have holes respectively, the two holes are coaxial with the central hole 10 of the base 1, and the ring belt camera connecting rod 14 passes through the other end holes of the first crossbeam 3 and the second crossbeam 5 The panoramic ring camera 11 is installed at the lower end of the ring camera connecting rod 14, and the panoramic ring camera 11 is equipped with a downward miniature laser rangefinder probe 12, and the miniature laser rangefinder probe 12 is used for distance measurement with a miniature laser with a display screen. The instrument host 13 is connected, and the upper end of the ring belt camera connecting rod 14 has a groove 7 for installing the extension rod 15. There are three holes on the side of the groove 7. Above the two beams 5, the gears in the transmission system 4 are meshed with the racks on the side of the belt camera connecting rod 14, so that the belt camera connecting rod 14 drives the panoramic belt camera 11 to move vertically in the center hole 10 of the base 1. , and move down, the panoramic ring belt camera 11 is connected with the computer by cables. the

The side of the extension rod 15 has a rack, and one end of the extension rod 15 protrudes 17, and the side of the protuberance 17 has three fixing holes 16, and one end of the extension rod 15 protrudes 17 into the groove on the upper end of the ring belt camera connecting rod 14 7, with three fastening screws 6 locking into one. the

The transmission system 4 is composed of a stepping motor, a gear mounted on the shaft of the stepping motor and a ratchet and pawl mechanism. the

The steps of this method are as follows:

1) Device positioning: Move the device above the vertical circular soil hole of the soil to be tested, completely align the round hole of the base of the device with the top of the hole, and adjust the two horizontal adjustment screws of the device seat to make the base of the device level;

2) Positioning of the panoramic ring camera: the reading of the miniature laser rangefinder is reset to zero; the stepper motor drives the connecting rod of the ring belt camera through the rack and pinion drive device to drive the panoramic ring camera to move vertically downward, when the miniature laser rangefinder When the displayed distance reading is exactly 1cm larger than the sum of the camera body length and the lens length of the panoramic ring belt, turn off the power supply of the stepping motor, and the position of the panoramic belt camera is the starting position of taking pictures; from here, the panoramic belt Every 5cm vertical movement of the camera is a photographing position, and the vertical movement of the panoramic ring camera is automatically controlled to the position to be photographed by the pulse signal applied to the stepping motor. the

3) Shooting images: At each photographing position, the panoramic ring camera is controlled by the computer to shoot the panoramic ring images, and the photos are stored in the computer hard disk in BMP format. the

When taking pictures, the distance count of the host 13 of the micro laser rangefinder with display screen is cleared, the protrusion 17 of the extension rod 15 is matched with the groove 7 of the connecting rod 14 of the ring belt camera, and three fastening screws are used. 6 Fasten the two together through the fixing hole 16. Loosen the pawl in the transmission system 4, loosen the braking device of the transmission system, and apply a reflected pulse to the stepping motor of the transmission system 4, so that when the stepping motor is running, the ring belt camera connecting rod 14 moves vertically downward , to drive the panoramic ring belt camera 11 to move vertically downward. During this process, the host 13 of the miniature laser rangefinder receives the distance information transmitted by the probe 12. When the reading on the display screen on the host 13 of the miniature laser rangefinder is just greater than the When the length of the belt camera 11 (comprising the length of the fuselage and the lens) was 1cm, the power supply of the transmission system 4 stepping motors was closed. Can fall freely, just because of gravity, the ratchet of transmission system can automatically engage ratchet, produces a reaction force, stops panoramic belt camera 11, belt camera connecting rod 14 and extension rod 15 from continuing to move vertically downwards, at this moment The position of is the initial position for panoramic ring photography. the

Apply a positive electric pulse to the stepper motor passed to the system 4, so that the ring belt camera connecting rod 14 and the extension rod 15 move vertically upwards, and simultaneously drive the panoramic ring belt camera 11 to move vertically upwards, and the moving distance is determined by the pulse. Size decides. the

Panoramic ring belt camera 11 starts at 1cm away from the bottom of the soil hole, and takes a picture every time it moves up vertically by 5cm. Panoramic ring belt camera 11 is connected with computer by cable, and is controlled by computer and finishes taking pictures every time, and photo is stored in computer hard disk with BMP format. the

The steps of data processing are as follows:

1) Image unfolding: the panoramic ring image is unfolded into a rectangular image by using the linearization method, which is divided into two processes: linearization in the tangential direction and linearization in the radial direction. the

①Linearization in the tangential direction: the annulus image is based on the Flat Cylinder Perspective (FCP) perspective method, and the principle of tangential direction expansion is shown in Figure 4. the

Therefore, according to the principle of FCP imaging, all straight lines parallel to the optical axis on the cylindrical surface converge at one point in the ring image, and all points forming an angle θ to the optical axis form a circle with a radius ρ after imaging, where:

ρ=kθ (1)

In the formula, k is a linear coefficient, determined by k=Δρ/Δθ, as shown in Figure 5. the

In Figure 4, OO' is the optical axis of the system, and O is the entrance pupil of the system. For a certain line segment AB, the angle formed by two points A and B connecting point O to the optical axis is θ. If the plane ABC is perpendicular to the optical axis, then The angle formed by any point of arc ACB connecting point O to the optical axis is θ. , its image is arc A′C′B′ (as shown in Figure 5), which is a section of arc with radius ρ=kθ, connecting AB, any point P on it, connecting OP, and setting the angle formed between it and O O′ is θ′, and its image is P′ in Fig. 5, then:

P'=kθ' (2) Then P' must not be on the arc A'C'B'. Let the radius of the cylinder be r, the distance from O ₁ to AB be d, and O ₁ P ₁ be l, as shown in Figure 6, then:

l＝d/sin(π-arcsin(d/r)-a+γ （3）

θ′＝arctan(l/h) （4）

In the formula, h is the distance of _OO2 . From h=r/tanθ, substituting formula (3) into formula (4), we can get:

${\mathrm{<span\; class="notranslate">\; \&theta;</span>}}^{<span\; class="notranslate">\; \&prime;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; arctan</span>}<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; the\; tan</span>}\mathrm{<span\; class="notranslate">\; \&theta;</span>}}{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}\mathrm{<span\; class="notranslate">\; sin</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; arcsin</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; d</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&alpha;</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 5</span>}<span\; class="notranslate">\; )</span>$

② Linearization in the radial direction. Since the panoramic ring image is sometimes not linear in the radial direction, the rectangular image obtained in ① is stretched in the vertical direction, which is called radial linearization. the

Since the FCP projection method follows the f-θ theory, the panoramic ring image of equidistant ring lines on the cylindrical surface is a ring whose spacing gradually increases as the radius increases. Therefore, the image developed tangentially also needs to be expanded radially. The traditional imaging image height satisfies the f-tanθ relationship, so the image height h′ after expansion and the image height h of the original ring image satisfy:

h′=h tanθ/θ

The rectangular image after radial and tangential expansion is stored in the computer in BMP format. the

2) Image stitching: start from the first image at the top of the soil hole according to the shooting position, and in the order from top to bottom, combine four unfolded rectangular images of every four consecutive shooting positions in Photoshop CS5 Using the function of automatic image stitching, stitching into a large image in order from top to bottom. The spliced images are stored in the computer in BMP format. the

3) Image similarity calculation: Calculate the correlation between the expanded image mosaic and the texture features of the four standard images to measure the similarity between images. the

① Calculate the co-occurrence matrix of the image:

A(i, j) represents the number of pairs of pixels whose gray values are i-1 and j-1 respectively in the image where the difference distance is (a, b). Normalize A(i, j):

$\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; A</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; /</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\mathrm{<span\; class="notranslate">\; A</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 7</span>}<span\; class="notranslate">\; )</span>$

In the formula, P(i, j) is a matrix element of a 256*256 two-dimensional co-occurrence matrix. The calculation results are stored on the computer hard disk. the

②Calculation of image texture features:

Extract eigenvalues representing image textures from the co-occurrence matrix, including:

A. energy

$\mathrm{<span\; class="notranslate">\; E.</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\mathrm{<span\; class="notranslate">\; P</span>}{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 8</span>}<span\; class="notranslate">\; )</span>$

B. Contrast

$\mathrm{<span\; class="notranslate">\; I</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 9</span>}<span\; class="notranslate">\; )</span>$

C. Information entropy

$\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; -</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; log</span>}\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 10</span>}<span\; class="notranslate">\; )</span>$

D. Inverse gap

$\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{\mathrm{<span\; class="notranslate">\; <figure-callout\; id="1"\; label="j"\; filenames="DEST\_PATH\_HDA00002513517400011.png"\; state="\{\{state\}\}">j</figure-callout></span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 11</span>}<span\; class="notranslate">\; )</span>$

E. Correlation

$\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}\mathrm{<span\; class="notranslate">\; iP</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; \&mu;</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}{\mathrm{<span\; class="notranslate">\; \&mu;</span>}}_{\mathrm{<span\; class="notranslate">\; the\; y</span>}}}{{{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}{{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 12</span>}<span\; class="notranslate">\; )</span>$

In the formula, μ _x and μ _y are mean differences, ${\mathrm{\&mu;}}_x=\underset{i}{\mathrm{\&Sigma;}}i\underset{j}{\mathrm{\&Sigma;}}P(i,j),$ ${\mathrm{\&mu;}}_{\mathrm{the\; y}}=\underset{j}{\mathrm{\&Sigma;}}j\underset{i}{\mathrm{\&Sigma;}}P(i,j),$ σ _x , σ _y are standard deviations, ${\mathrm{\&sigma;}}_x=\underset{i}{\mathrm{\&Sigma;}}{(1-{\mathrm{\&mu;}}_x)}^2\underset{j}{\mathrm{\&Sigma;}}P(i,j),$ $\mathrm{\&sigma;y}=\underset{j}{\mathrm{\&Sigma;}}{(1-{\mathrm{\&mu;}}_{\mathrm{the\; y}})}^2\underset{i}{\mathrm{\&Sigma;}}P(i,j).$

The above five texture features form a texture feature vector (E, I, S, H, R), which is stored in the computer hard disk for correlation calculation. the

③Calculation of correlation

Use the formula (13) to calculate the correlation between the stitched image and the four soil type standard images by using the texture feature vectors of one mosaic image and four soil type standard images calculated in ②:

$\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{{\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="x\; i"\; filenames="DEST\_PATH\_HDA00002513517400011.png"\; state="\{\{state\}\}">x</figure-callout></span><figure-callout\; id="2"\; label="x\; i"\; filenames="DEST\_PATH\_HDA00002513517400011.png"\; state="\{\{state\}\}">\; </figure-callout>}}_{\mathrm{<span\; class="notranslate">\; </span>}}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 13</span>}<span\; class="notranslate">\; )</span>$

In the formula, r is the correlation, the larger r is, the more similar the two images are, and r=1, indicating that the two images are exactly the same. The correlation calculation results are shown in Table 1. the

4) Rapid identification of soil types: According to the attached table 1, it can be concluded that the correlation between the mosaic image and the first standard image is 0.85, which is larger than the others, indicating that the similarity between the two images is greater than that of the others. That is to say, the soil type corresponding to the spliced image is closer to the soil type corresponding to the first standard image, so as to realize the rapid discrimination of the soil type. the

5) The whole calculation is realized by Matlab programming. the

Table 1 Correlation Calculation Results

standard chart similarity Part 1 0.85 Part 2 0.64 3rd picture 0.23 4th picture 0.26

Claims (3)

1. device that utilizes the quick anticipation soil types of overall view ring belt Photographic technique, it is characterized in that: the base (1) in circle has center pit (10), pillar (2) is vertically fixed on the base (1), install and fix screw (18) and set screw (8) below the base (1) and be the equilateral triangle layout, glass horizontal bubble (10) is fixed on above the base (1), one stomidium of first crossbeam (3) and second cross beam (5) is separately fixed on the pillar (2) from bottom to up, the other end of first crossbeam (3) and second cross beam (5) has the hole, two holes are coaxial with base (1) center pit (10), endless belt camera connecting link (14) passes another stomidium of first crossbeam (3) and second cross beam (5), overall view ring belt camera (11) is installed in endless belt camera connecting link (14) lower end, the outer miniature laser stadimeter probe (12) that is equipped with down of overall view ring belt camera (11), miniature laser stadimeter probe (12) is connected with band display screen miniature laser stadimeter main frame (13) by cable, endless belt camera connecting link (14) upper end has the groove (7) that extension rod (15) is installed, band display screen miniature laser stadimeter main frame (13) and kinematic train (4) are contained in respectively above the second cross beam (5), gear in the kinematic train (4) is meshed with endless belt camera connecting link (14) side tooth bar, make endless belt camera connecting link (14) drive overall view ring belt camera (11) and in base (1) center pit (10), do the upper of vertical direction, lower movement, overall view ring belt camera (11) links by cable and computing machine.

2. a kind of device that utilizes the quick anticipation soil types of overall view ring belt Photographic technique according to claim 1, it is characterized in that: there is tooth bar described extension rod (15) side, and groove (7) internal locking that the end projection (17) of extension rod (15) is inserted endless belt camera connecting link (14) upper end is integral.

3. a kind of device that utilizes the quick anticipation soil types of overall view ring belt Photographic technique according to claim 1 is characterized in that: described kinematic train (4) is comprised of stepper motor, the gear and the ratchet and pawl arrangement that are installed on the step motor shaft.

Images