CN113502721A - Pavement performance determination method and system based on pavement texture - Google Patents

Abstract

The invention provides a pavement performance determination method and system based on pavement texture. The method includes acquiring a pavement image to be tested; determining the image coordinates and elevation data of each pixel in the pavement image to be tested; The image coordinates of the pixel points divide the road to be tested into multiple textures; according to the elevation data, the characteristic data of each texture in the road to be measured is determined; according to the deviation coefficient and distribution coefficient, the directional characteristics of each texture in the road to be measured are determined According to the roughness coefficient, determine the roughness feature type of each texture in the pavement to be tested; determine the performance of the pavement to be tested according to the directional feature type and roughness feature type of each texture in the pavement to be tested. By calculating the deviation coefficient, distribution coefficient and roughness coefficient, the invention can accurately determine the directional feature type and roughness feature type of each texture in the pavement to be measured, thereby improving the accuracy of pavement property determination.

Description

A method and system for determining pavement performance based on pavement texture

technical field

The invention relates to the technical field of pavement texture analysis, in particular to a pavement performance determination method and system based on pavement texture.

Background technique

In order to develop and design high-performance asphalt pavement, it is necessary to analyze and evaluate the surface texture of the pavement. Invention patent CN107796325B discloses a measurement method and measurement system for the depth of pavement texture structure. After obtaining the elevation value of pavement texture, the method takes the sand-laying plane as the reference plane, and extracts the gap between the surface and the reference plane. The quotient of the volume of the pavement to be measured is divided by the pavement texture depth. The invention patent CN111692988A discloses a pavement structure depth detection system. After obtaining the pavement structure depth test value by the laser section scanning method, the structure depth measured by the manual sand laying method is used as the standard, and the result measured by the laser is used to fit the curve. Correction.

However, these two methods both extract an abstract elevation index from the pavement texture. Although the latter has modified it, the characteristics of the pavement texture are still relatively simple, ignoring the contour details of the pavement texture itself, so it is impossible to The comprehensive and systematic feature extraction of pavement texture results in inaccurate classification of textures, which in turn leads to errors in the analysis of asphalt pavement performance.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a pavement performance determination method and system based on pavement texture, which can accurately determine the directional feature type and roughness feature type of each texture in the pavement to be measured, thereby improving the accuracy of pavement property determination.

For achieving the above object, the present invention provides the following scheme:

A pavement performance determination method based on pavement texture, comprising:

Obtain the road surface image to be tested;

Determine the image coordinates and elevation data of each pixel in the road image to be tested;

According to the image coordinates of each pixel in the image of the road to be tested, the road to be tested is divided into multiple textures; the ordinates of the image coordinates of all pixels in the same texture are equal;

According to the elevation data, the characteristic data of each texture in the road surface to be measured is determined; the characteristic data includes a deviation coefficient, a distribution coefficient and a roughness coefficient;

According to the deviation coefficient and the distribution coefficient, determine the directional feature type of each texture in the road surface to be tested; the directional feature types include positive texture, negative texture and symmetrical texture;

According to the roughness coefficient, determine the roughness feature type of each texture in the road surface to be tested; the roughness feature type includes rough texture and smooth texture;

The performance of the pavement to be tested is determined according to the directional feature type and the roughness feature type of each texture in the pavement to be tested.

Optionally, before dividing the road surface to be measured into multiple textures according to the image coordinates of each pixel in the road surface image to be measured, the method further includes:

Using the formula z' _i =z _i -(Ax+By+C), the elevation data of each pixel in the road image to be measured is subjected to slope correction processing to obtain once-corrected elevation data;

When there is a missing value or an outlier value in the primary corrected elevation data, performing interpolation processing on the primary corrected elevation data to obtain secondary corrected elevation data;

Among them, _zi ' is the corrected elevation value of the i-th pixel point (x, y) on the road image to be tested, and _zi is the elevation value of the i-th pixel point (x, y) on the road image to be tested before correction , A, B, and C are all constants.

Optionally, determining the characteristic data of each texture in the road surface to be measured according to the elevation data specifically includes:

Determine any texture as the current texture;

计算所述当前纹理的偏离系数；According to the elevation data of the current texture, use the formula

calculating the deviation coefficient of the current texture;

Determine that the ratio of the number of points whose elevation data is greater than the depth threshold in the current texture to the number of all points in the current texture is the distribution coefficient of the current texture;

计算所述当前纹理的粗糙系数；According to the elevation data of the current texture, use the formula

calculating the roughness coefficient of the current texture;

Z(x)为同一条纹理中图像坐标的横坐标为x的像素点的高程值，Q_ro为粗糙系数，A_N为标准化后的纹理幅值，λ_N为标准化后的纹理波长。Among them, R _sk is the deviation coefficient, R _q is the arithmetic square root of the square of the texture elevation deviation,

Z(x) is the elevation value of the pixel whose abscissa of the image coordinate is x in the same texture, Q _ro is the roughness coefficient, _AN is the normalized texture amplitude, and λ _N is the normalized texture wavelength.

Optionally, determining the directional feature type of each texture in the road surface to be measured according to the deviation coefficient and the distribution coefficient specifically includes:

Determine whether the current texture is a positive texture according to the deviation coefficient and distribution coefficient of the current texture; the condition for determining the current texture to be a positive texture is that the deviation coefficient of the current texture is greater than a first threshold and the current texture is The distribution coefficient is greater than the second threshold;

When the current texture is not a positive texture, determine whether the current texture is a negative texture according to the deviation coefficient of the current texture and the distribution coefficient; the condition for determining that the current texture is a negative texture is that the current texture is a negative texture the deviation coefficient is less than the first threshold and the distribution coefficient of the current texture is less than the second threshold;

When the current texture is neither a positive texture nor a negative texture, it is determined that the current texture is a symmetric texture.

Optionally, determining the roughness feature type of each texture in the road surface to be measured according to the roughness coefficient specifically includes:

Judging whether the roughness coefficient of the current texture is greater than a third threshold, and obtaining a judgment result;

If the judgment result is yes, determine that the current texture is a rugged texture;

If the judgment result is no, it is determined that the current texture is a smooth texture.

A pavement performance determination system based on pavement texture, comprising:

The road surface image module to be measured is used to obtain the road surface image to be measured;

a data acquisition module for determining the image coordinates and elevation data of each pixel in the road image to be measured;

a texture division module, configured to divide the road surface to be measured into a plurality of textures according to the image coordinates of each pixel point in the road surface image to be measured; the ordinates of the image coordinates of all pixels in the same texture are equal;

a feature data determination module, configured to determine feature data of each texture in the road surface to be measured according to the elevation data; the feature data includes a deviation coefficient, a distribution coefficient and a roughness coefficient;

a directional feature type determination module, configured to determine the directional feature type of each texture in the road surface to be tested according to the deviation coefficient and the distribution coefficient; the directional feature types include positive texture, negative texture and symmetrical texture;

a rough feature type determination module, configured to determine the rough feature type of each texture in the road surface to be tested according to the roughness coefficient; the rough feature types include rough textures and smooth textures;

The performance determination module is used for determining the performance of the road surface to be tested according to the directional feature type and the roughness feature type of each texture in the road surface to be tested.

Optionally, the system further includes:

The slope correction module is used for using the formula _zi '= _zi -(Ax+By+C) to perform slope correction processing on the elevation data of each pixel point in the road image to be measured, to obtain once corrected elevation data ;

an interpolation processing module, configured to perform interpolation processing on the first-corrected elevation data when there is a missing value or an outlier in the primary-corrected elevation data to obtain secondary-corrected elevation data;

Among them, z' _i is the corrected elevation value of the _i -th pixel point (x, y) on the road image to be tested, and zi is the elevation value of the i-th pixel point (x, y) on the road image to be tested before correction , A, B, and C are all constants.

Optionally, the feature data determination module specifically includes:

The current texture determination unit is used to determine any texture as the current texture;

计算所述当前纹理的偏离系数；The deviation coefficient calculation unit is used for using the formula according to the elevation data of the current texture

calculating the deviation coefficient of the current texture;

a distribution coefficient determination unit, configured to determine that the ratio of the number of points with elevation data greater than a depth threshold in the current texture to the number of all points in the current texture is the distribution coefficient of the current texture;

计算所述当前纹理的粗糙系数；The roughness coefficient calculation unit is used for using the formula according to the elevation data of the current texture

calculating the roughness coefficient of the current texture;

Z(x)为同一条纹理中图像坐标的横坐标为x的像素点的高程值，Q_ro为粗糙系数，A_N为标准化后的纹理幅值，λ_N为标准化后的纹理波长。Among them, R _sk is the deviation coefficient, R _q is the arithmetic square root of the square of the texture elevation deviation,

Z(x) is the elevation value of the pixel whose abscissa of the image coordinate is x in the same texture, Q _ro is the roughness coefficient, _AN is the normalized texture amplitude, and λ _N is the normalized texture wavelength.

Optionally, the direction feature type determination module specifically includes:

A positive texture determination unit, configured to determine whether the current texture is a positive texture according to the deviation coefficient and distribution coefficient of the current texture; the condition for determining that the current texture is a positive texture is that the deviation coefficient of the current texture is greater than the first texture a threshold and the distribution coefficient of the current texture is greater than a second threshold;

A negative texture determination unit, configured to determine whether the current texture is a negative texture according to the deviation coefficient of the current texture and the distribution coefficient when the current texture is not a positive texture; determine whether the current texture is a negative texture The condition is that the deviation coefficient of the current texture is less than the first threshold and the distribution coefficient of the current texture is less than the second threshold;

A symmetrical texture determination unit, configured to determine that the current texture is a symmetrical texture when the current texture is neither a positive texture nor a negative texture.

Optionally, the rough feature type determination module specifically includes:

a judgment unit, used for judging whether the roughness coefficient of the current texture is greater than a third threshold, and obtaining a judgment result; if the judgment result is yes, call the rugged texture determination unit; if the judgment result is no, call the smooth texture determine the unit;

a rugged texture determination unit, configured to determine that the current texture is a rugged texture;

A flat texture determination unit, configured to determine that the current texture is a flat texture.

According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

The invention provides a pavement performance determination method and system based on pavement texture, and the method includes acquiring a pavement image to be tested; determining the image coordinates and elevation data of each pixel in the pavement image to be tested; According to the image coordinates of each pixel point, the road to be tested is divided into multiple textures; according to the elevation data, the characteristic data of each texture in the road to be measured is determined; the characteristic data includes deviation coefficient, distribution coefficient and roughness coefficient; according to the deviation coefficient and distribution coefficient to determine the directional feature type of each texture in the pavement to be tested; determine the roughness feature type of each texture in the pavement to be tested according to the roughness coefficient; determine the directional feature type and roughness feature type of each texture in the pavement to be tested The performance of the road surface to be tested. By calculating the deviation coefficient, distribution coefficient and roughness coefficient, the invention can accurately determine the directional feature type and roughness feature type of each texture in the pavement to be measured, thereby improving the accuracy of pavement property determination.

Description of drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings required in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some of the present invention. In the embodiments, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without creative labor.

1 is a flowchart of a method for determining road surface performance based on road surface texture in an embodiment of the present invention;

2 is a schematic diagram of a positive texture elevation in an embodiment of the present invention;

3 is a schematic diagram of a negative texture elevation in an embodiment of the present invention;

4 is a positive texture elevation distribution diagram in an embodiment of the present invention;

5 is a negative texture elevation distribution diagram in an embodiment of the present invention;

6 is a schematic diagram of a gentle texture elevation in an embodiment of the present invention;

FIG. 7 is a schematic diagram of a rugged texture elevation in an embodiment of the present invention;

FIG. 8 is a schematic structural diagram of a pavement performance determination system based on pavement texture in an embodiment of the present invention.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

The purpose of the present invention is to provide a pavement performance determination method and system based on pavement texture, which can accurately determine the directional feature type and roughness feature type of each texture in the pavement to be measured, thereby improving the accuracy of pavement property determination.

In order to make the above objects, features and advantages of the present invention more clearly understood, the present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.

1 is a flowchart of a method for determining pavement performance based on pavement texture in an embodiment of the present invention. As shown in FIG. 1 , the present invention provides a method for determining pavement performance based on pavement texture, including:

Step 101 : acquiring an image of the road surface to be tested;

Step 102: Determine the image coordinates and elevation data of each pixel in the road image to be measured;

Step 103: According to the image coordinates of each pixel point in the road surface image to be tested, the road surface to be tested is divided into multiple textures; the ordinates of the image coordinates of all pixels in the same texture are equal;

Step 104: According to the elevation data, determine the characteristic data of each texture in the road surface to be tested; the characteristic data includes deviation coefficient, distribution coefficient and roughness coefficient;

Step 105: Determine the directional feature type of each texture in the road surface to be tested according to the deviation coefficient and the distribution coefficient; the directional feature types include positive texture, negative texture and symmetrical texture;

Step 106: According to the roughness coefficient, determine the roughness feature type of each texture in the road surface to be tested; the roughness feature type includes rough texture and smooth texture;

Step 107: Determine the performance of the pavement to be tested according to the directional feature type and rough feature type of each texture in the pavement to be tested.

In addition, before step 103, the method for determining pavement performance based on pavement texture provided by the present invention further includes:

Using the formula z' _i =z _i -(Ax+By+C), the elevation data of each pixel in the road surface image to be measured is subjected to slope correction processing to obtain one-time corrected elevation data;

When there are missing values or outliers in the primary corrected elevation data, interpolate the primary corrected elevation data to obtain the secondary corrected elevation data;

Among them, _zi ' is the corrected elevation value of the i-th pixel point (x, y) on the road image to be tested, and _zi is the elevation value of the i-th pixel point (x, y) on the road image to be tested before correction , A, B, and C are all constants.

Step 104 specifically includes:

Determine any texture as the current texture;

计算当前纹理的偏离系数；According to the elevation data of the current texture, use the formula

Calculate the deviation coefficient of the current texture;

Determine the ratio of the number of points whose elevation data is greater than the depth threshold in the current texture to the number of all points in the current texture as the distribution coefficient of the current texture;

计算当前纹理的粗糙系数；According to the elevation data of the current texture, use the formula

Calculate the roughness coefficient of the current texture;

Z(x)为同一条纹理中图像坐标的横坐标为x的像素点的高程值，Q_ro为粗糙系数，A_N为标准化后的纹理幅值，λ_N为标准化后的纹理波长。Among them, R _sk is the deviation coefficient, R _q is the arithmetic square root of the square of the texture elevation deviation,

Z(x) is the elevation value of the pixel whose abscissa of the image coordinate is x in the same texture, Q _ro is the roughness coefficient, _AN is the normalized texture amplitude, and λ _N is the normalized texture wavelength.

Step 105 specifically includes:

According to the deviation coefficient and distribution coefficient of the current texture, determine whether the current texture is a positive texture; the condition for determining that the current texture is a positive texture is that the deviation coefficient of the current texture is greater than the first threshold and the distribution coefficient of the current texture is greater than the second threshold; The elevation data of a pixel is shown in Figure 2, where the abscissa is the abscissa of the pixel in the same texture, and the ordinate is the elevation value.

When the current texture is not a positive texture, determine whether the current texture is a negative texture according to the deviation coefficient and distribution coefficient of the current texture; the condition for determining that the current texture is a negative texture is that the deviation coefficient of the current texture is less than the first threshold and the distribution coefficient of the current texture is less than the second threshold; the elevation data of each pixel of the negative texture is shown in Figure 3, where the abscissa is the abscissa of the pixel in the same texture, and the ordinate is the elevation value.

When the current texture is neither a positive texture nor a negative texture, it is determined that the current texture is a symmetrical texture.

Step 106 specifically includes:

Determine whether the roughness coefficient of the current texture is greater than the third threshold, and obtain the judgment result;

If the judgment result is yes, it is determined that the current texture is a rugged texture; the elevation data of each pixel point of the rugged texture is shown in Figure 7, where the abscissa is the abscissa of the pixel in the same texture, and the ordinate is the elevation value.

If the judgment result is no, it is determined that the current texture is a smooth texture. The elevation data of each pixel of the smooth texture is shown in Figure 6, where the abscissa is the abscissa of the pixel in the same texture, and the ordinate is the elevation value.

Specifically, the specific steps of the method for determining pavement performance based on pavement texture provided by the present invention are as follows:

Step 1: Use a 3D texture scanner to scan the surface of the road section to be tested to obtain texture data.

A high-speed blue-light 3D laser contour sensor is used to scan the road to be tested for texture, and the texture data of the target section is collected (texture data can be presented in three forms: contour, image and point cloud). Specifically, connect the computer and the high-speed blue-light 3D laser profile sensor through the IO cable. After repeating the measurement of the target segment to obtain multiple frames of images, view the historical playback from the web interface, select the frame with higher integrity and definition, and output It is the data in CSV format, which contains the parameter configuration information of the high-speed blue 3D laser profile sensor, the measured point cloud data information and the measurement value information. The sensor parameter configuration information mainly includes the resolution in the three-dimensional direction, the moving speed of the scanning probe along the Y direction, the coordinates of the starting and ending points of the scanning path, and the scanning field of view and measurement range, etc.; the point cloud data information includes the three-dimensional coordinate information of the measuring point. Measurement value and judgment result, as well as statistical information of row and column data volume, etc.

Step 2: Processing of Texture Data

2.1. Use the least squares method to fit the texture data on a plane, and use the elevation processing method to correct the slope;

If the measured road surface has a certain slope relative to the horizontal plane, the texture data needs to be corrected. First, it is necessary to perform plane fitting on the texture data, which can be achieved by the least squares method. Then its equation can be obtained: _zi =Ax+By+C. Because the maximum longitudinal slope does not exceed 8%, an approximate elevation processing method can be adopted, and only the elevation data _zi can be processed to obtain the elevation data z′ _i = _zi -(Ax+By+C) after slope correction.

2.2, use Lagrangian interpolation to fill in missing values;

If there are missing values in the collected texture data due to various reasons, methods such as fixed value filling, missing retention, interpolation filling and model filling can be selected according to the causes; if the subsequent data processing is not affected, the missing values do the processing. If the missing is caused by systematic factors, such as a gap in the road surface, it can be filled with a fixed value and replaced with a value far lower than the minimum texture elevation; if the missing is caused by accidental factors, such as instrument failure or human operation, the number of missing values is relatively large. Lagrangian interpolation can be used for filling when it is small. If the elevation function z _{=f(x) is known, the elevations z 0 , z 1 , .} A polynomial P _n (x) with n+1 points and the highest degree less than n satisfies P _n (x _k )=y _k , k=0,1,...,n; for the elevation at point i where the missing value is located, available P _n (i) is used as an approximation of f(i) and is interpolated.

2.3, use the absolute median difference algorithm to judge the outliers, and then use the Lagrangian interpolation method to fill and process the outliers.

The outliers can be divided into two types, one is the pseudo-abnormality reflecting the real condition of the road surface, and the other is the true abnormality caused by instrument failure or operation error. The former usually does not need to be processed, and the latter should be re-measured if the number is too large. Outliers are judged according to the absolute median difference algorithm. First calculate the median of the target data set, then calculate the absolute deviation value of each data in the data set from the median, and then determine the median of multiple absolute deviation values. And determine the data with the absolute deviation value greater than the median of the absolute deviation value as outliers, and use the same processing method as the missing value for correction.

Step 3: Classification of Textures

According to the relative relationship between the pavement texture and the pavement reference plane, the texture can generally be divided into a positive texture (Positive Texture) and a negative texture (Negative Texture). The positive texture is expressed as a protrusion relative to the reference plane of the road surface, and the negative texture is expressed as a depression relative to the reference plane of the road surface.

Whether the pavement texture is positive or negative can be determined by the deviation coefficient R _sk of the elevation distribution characteristic index and the distribution coefficient P _R/2 . The deviation coefficient R _sk describes the symmetry of the pavement texture elevation distribution, that is, the texture is generally higher or lower than the reference surface; the distribution coefficient P _R/2 describes the cumulative percentage of elevation corresponding to 1/2 the maximum texture depth R .

According to the roughness of the texture itself, according to the wavelength λ and the amplitude A of the texture, the texture can be divided into a smooth texture and a rough texture. Where the texture wavelength λ is longer and the amplitude A is smaller, it is a smooth texture; on the contrary, the texture wavelength λ is shorter and the amplitude A is larger, it is a rugged texture.

3.1 Feature extraction based on texture classification:

3.1.1 Deviation coefficient R _sk

The definition of the deviation coefficient R _sk is as follows:

The deviation coefficient R _sk represents the cubic arithmetic mean of the texture elevation Z(x) within the sample length. Taking the first threshold as 0, when R _sk = 0, the texture elevation is normally distributed; when R _sk < 0, the texture elevation is relatively low relative to the reference plane, which is a negative texture; when R _sk > 0, the texture elevation is relatively The base surface is high, and it is a positive texture.

3.1.2 Distribution coefficient P _R/2

According to the definition, when extracting the distribution coefficient P _R/2 , the cumulative distribution function of the pavement texture elevation should be drawn first, and the maximum texture depth R is determined according to the cumulative distribution function of the elevation, then the cumulative corresponding to R/2 (depth threshold) The distribution percentage is the distribution coefficient P _R/2 . The elevation distributions of positive and negative textures are shown in Fig. 4 and Fig. 5, respectively. Among them, the abscissa is the cumulative distribution rate, and the ordinate is the elevation value.

Take the second threshold as 50%, when P _R/2 > 50%, it means that the elevation of the section is mostly higher than R/2, showing negative texture; on the contrary, when P _R/2 <50%, it means that the elevation of the section is mostly lower than R /2, showing a positive texture.

In the present invention, both the deviation coefficient R _sk and the distribution coefficient P _R/2 can independently determine the positive and negative textures. When the two judgment results conflict, it is considered that the texture does not have obvious positive and negative characteristics, and can be classified into another category. , called "symmetric texture".

3.1.3 Roughness factor

Normalize the texture wavelength λ and the amplitude A. Taking the texture wavelength as an example, the two-dimensional surface texture line of the pavement is regarded as a random function, and the horizontal distance between two repeated textures is defined as a wavelength λ _i . Then the normalized wavelength λ _N can be obtained by the following formula:

in,

为纹理波长的均值，s_λ为纹理波长的标准差，λ_i为同一条纹理中第i个像素点的波长，n为同一条纹理中像素点的数量。In the formula,

is the mean value of texture wavelength, s _λ is the standard deviation of texture wavelength, λ _i is the wavelength of the ith pixel in the same texture, and n is the number of pixels in the same texture.

In the same way, the normalized amplitude A _N can be obtained.

Define roughness coefficient (Roughness, Q _ro )

Taking the third threshold as 1, when the roughness coefficient Q _ro ≤ 1, the road texture is determined to be a smooth texture; when the rough coefficient Q _ro >1, the road texture is determined to be a rough texture.

FIG. 8 is a schematic structural diagram of a pavement performance determination system based on pavement texture in an embodiment of the present invention. As shown in FIG. 8 , the present invention also provides a pavement texture-based pavement performance determination system, including:

The road surface image module 801 to be measured is used for acquiring the road surface image to be measured;

A data acquisition module 802, configured to determine the image coordinates and elevation data of each pixel in the road surface image to be measured;

The texture division module 803 is used to divide the road to be tested into multiple textures according to the image coordinates of each pixel in the image of the road to be tested; the ordinates of the image coordinates of all pixels in the same texture are equal;

The characteristic data determination module 804 is used for determining characteristic data of each texture in the road surface to be measured according to the elevation data; the characteristic data includes deviation coefficient, distribution coefficient and roughness coefficient;

The directional feature type determination module 805 is used to determine the directional feature type of each texture in the road surface to be tested according to the deviation coefficient and the distribution coefficient; the directional feature types include positive texture, negative texture and symmetrical texture;

a rough feature type determination module 806, configured to determine the rough feature type of each texture in the road surface to be tested according to the roughness coefficient; the rough feature type includes rough texture and smooth texture;

The performance determination module 807 is configured to determine the performance of the road surface to be tested according to the directional feature type and the roughness feature type of each texture in the road surface to be tested.

The pavement performance determination system based on pavement texture provided by the present invention further includes:

The slope correction module is used for using the formula _zi '= _zi -(Ax+By+C) to perform slope correction processing on the elevation data of each pixel point in the road surface image to be measured, and obtain once-corrected elevation data;

The interpolation processing module is used to perform interpolation processing on the first corrected elevation data when there are missing values or outliers in the first corrected elevation data to obtain the second corrected elevation data;

Among them, _zi ' is the corrected elevation value of the i-th pixel point (x, y) on the road image to be tested, and _zi is the elevation value of the i-th pixel point (x, y) on the road image to be tested before correction , A, B, and C are all constants.

Specifically, the feature data determination module 804 specifically includes:

The current texture determination unit is used to determine any texture as the current texture;

计算当前纹理的偏离系数；The deviation coefficient calculation unit is used to use the formula according to the elevation data of the current texture

Calculate the deviation coefficient of the current texture;

a distribution coefficient determination unit, used to determine the ratio of the number of points whose elevation data is greater than the depth threshold in the current texture to the number of all points in the current texture as the distribution coefficient of the current texture;

计算当前纹理的粗糙系数；The roughness coefficient calculation unit is used to use the formula according to the elevation data of the current texture

Calculate the roughness coefficient of the current texture;

Z(x)为同一条纹理中图像坐标的横坐标为x的像素点的高程值，Q_ro为粗糙系数，A_N为标准化后的纹理幅值，λ_N为标准化后的纹理波长。Among them, R _sk is the deviation coefficient, R _q is the arithmetic square root of the square of the texture elevation deviation,

Z(x) is the elevation value of the pixel whose abscissa of the image coordinate is x in the same texture, Q _ro is the roughness coefficient, _AN is the normalized texture amplitude, and λ _N is the normalized texture wavelength.

The direction feature type determination module 805 specifically includes:

The positive texture determination unit is used to determine whether the current texture is a positive texture according to the deviation coefficient and distribution coefficient of the current texture; the condition for determining that the current texture is a positive texture is that the deviation coefficient of the current texture is greater than the first threshold and the distribution coefficient of the current texture is greater than the second threshold;

The negative texture determination unit is used to determine whether the current texture is a negative texture according to the deviation coefficient and distribution coefficient of the current texture when the current texture is not a positive texture; the condition for determining that the current texture is a negative texture is that the deviation coefficient of the current texture is less than the first texture. threshold and the distribution coefficient of the current texture is less than the second threshold;

The symmetric texture determination unit is used to determine that the current texture is a symmetric texture when the current texture is neither a positive texture nor a negative texture.

The rough feature type determination module 806 specifically includes:

a judgment unit, used for judging whether the roughness coefficient of the current texture is greater than the third threshold value, and obtaining a judgment result; if the judgment result is yes, call the rough texture determination unit; if the judgment result is no, call the smooth texture determination unit;

The rugged texture determination unit is used to determine the current texture as a rugged texture;

The flat texture determination unit is used to determine the current texture as a flat texture.

The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the various embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant part can be referred to the description of the method.

In this paper, specific examples are used to illustrate the principles and implementations of the present invention. The descriptions of the above embodiments are only used to help understand the methods and core ideas of the present invention; meanwhile, for those skilled in the art, according to the present invention There will be changes in the specific implementation and application scope. In conclusion, the contents of this specification should not be construed as limiting the present invention.

Claims (10)

1. A method for determining pavement properties based on pavement texture, the method comprising:

acquiring a road surface image to be detected;

determining image coordinates and elevation data of each pixel point in the road surface image to be detected;

dividing the road surface to be detected into a plurality of textures according to the image coordinates of each pixel point in the road surface image to be detected; the vertical coordinates of the image coordinates of all the pixel points in the same texture are equal;

determining feature data of each texture in the road surface to be detected according to the elevation data; the characteristic data comprises a deviation coefficient, a distribution coefficient and a roughness coefficient;

determining the direction characteristic type of each texture in the road surface to be detected according to the deviation coefficient and the distribution coefficient; the direction feature types comprise positive texture, negative texture and symmetrical texture;

determining the roughness characteristic type of each texture in the road surface to be detected according to the roughness coefficient; the coarse feature types include a rough texture and a smooth texture;

and determining the performance of the road surface to be detected according to the direction characteristic type and the roughness characteristic type of each texture in the road surface to be detected.

2. The method for determining road surface performance based on road surface texture according to claim 1, before dividing the road surface to be measured into a plurality of textures according to the image coordinates of each pixel point in the road surface image to be measured, further comprising:

by the formula z'_i＝z_i- (Ax + By + C), and performing slope correction processing on the elevation data of each pixel point in the road surface image to be detected to obtain primarily corrected elevation data;

when the missing value or the outlier exists in the primarily corrected elevation data, performing interpolation processing on the primarily corrected elevation data to obtain secondarily corrected elevation data;

wherein, z'_iThe corrected elevation value, z, of the ith pixel point (x, y) on the road surface image to be detected_iA, B, C are constants for the elevation value of the ith pixel point (x, y) on the road surface image to be detected before correction.

3. The method for determining the road surface performance based on the road surface texture according to claim 1, wherein the determining the characteristic data of each texture in the road surface to be measured according to the elevation data specifically comprises:

determining any texture as a current texture;

using a formula based on the elevation data of the current texture

ComputingA deviation factor of the current texture;

determining the ratio of the number of points with higher range data larger than a depth threshold value in the current texture to the number of all points in the current texture as a distribution coefficient of the current texture;

using a formula based on the elevation data of the current texture

Calculating a roughness coefficient of the current texture;

wherein R is_skTo be a coefficient of deviation, R_qIs the arithmetic square root of the square of the texture elevation deviation,

z (x) is the elevation value of the pixel point with x as the abscissa of the image coordinate in the same fringe process, Q_roIs a roughness coefficient, A_NFor normalized texture amplitude, λ_NIs the normalized texture wavelength.

4. The method for determining the road surface performance based on the road surface texture according to claim 3, wherein the determining the direction feature type of each texture in the road surface to be measured according to the deviation coefficient and the distribution coefficient specifically comprises:

determining whether the current texture is a positive texture or not according to the deviation coefficient and the distribution coefficient of the current texture; determining that the current texture is a positive texture if a deviation coefficient of the current texture is greater than a first threshold and a distribution coefficient of the current texture is greater than a second threshold;

when the current texture is not the positive texture, determining whether the current texture is the negative texture or not according to the deviation coefficient and the distribution coefficient of the current texture; determining that the current texture is a negative texture if a deviation coefficient of the current texture is less than the first threshold and a distribution coefficient of the current texture is less than the second threshold;

determining the current texture as a symmetric texture when the current texture is neither a positive texture nor a negative texture.

5. The method for determining the road surface performance based on the road surface texture according to the claim 4, wherein the determining the roughness characteristic type of each texture in the road surface to be measured according to the roughness coefficient specifically comprises:

judging whether the rough coefficient of the current texture is larger than a third threshold value or not to obtain a judgment result;

if the judgment result is yes, determining that the current texture is a rugged texture;

and if the judgment result is negative, determining that the current texture is a smooth texture.

6. A pavement property determination system based on a texture of a pavement, the system comprising:

the to-be-detected road surface image module is used for acquiring a to-be-detected road surface image;

the data acquisition module is used for determining the image coordinates and the elevation data of each pixel point in the road surface image to be detected;

the texture dividing module is used for dividing the road surface to be detected into a plurality of textures according to the image coordinates of each pixel point in the road surface image to be detected; the vertical coordinates of the image coordinates of all the pixel points in the same texture are equal;

the characteristic data determining module is used for determining the characteristic data of each texture in the road surface to be detected according to the elevation data; the characteristic data comprises a deviation coefficient, a distribution coefficient and a roughness coefficient;

the direction characteristic type determining module is used for determining the direction characteristic type of each texture in the road surface to be detected according to the deviation coefficient and the distribution coefficient; the direction feature types comprise positive texture, negative texture and symmetrical texture;

the rough characteristic type determining module is used for determining the rough characteristic type of each texture in the road surface to be detected according to the rough coefficient; the coarse feature types include a rough texture and a smooth texture;

and the performance determining module is used for determining the performance of the road surface to be detected according to the direction characteristic type and the rough characteristic type of each texture in the road surface to be detected.

7. The system of claim 6, further comprising:

a slope correction module for utilizing the formula z'_i＝z_i- (Ax + By + C), and performing slope correction processing on the elevation data of each pixel point in the road surface image to be detected to obtain primarily corrected elevation data;

the interpolation processing module is used for carrying out interpolation processing on the primarily corrected elevation data to obtain secondarily corrected elevation data when a missing value or an outlier exists in the primarily corrected elevation data;

wherein, z'_iThe corrected elevation value, z, of the ith pixel point (x, y) on the road surface image to be detected_iA, B, C are constants for the elevation value of the ith pixel point (x, y) on the road surface image to be detected before correction.

8. The system of claim 6, wherein the characteristic data determining module specifically includes:

a current texture determining unit, configured to determine any texture as a current texture;

a deviation coefficient calculation unit for using a formula according to the elevation data of the current texture

Calculating a deviation coefficient of the current texture;

a distribution coefficient determining unit, configured to determine that a ratio of the number of points in the current texture, for which the height data is greater than the depth threshold, to the number of all points in the current texture is a distribution coefficient of the current texture;

a rough coefficient calculation unit for calculating the elevation data of the current texture by using a formula

Calculating a roughness coefficient of the current texture;

wherein R is_skTo be a coefficient of deviation, R_qIs the arithmetic square root of the square of the texture elevation deviation,

z (x) is the elevation value of the pixel point with x as the abscissa of the image coordinate in the same fringe process, Q_roIs a roughness coefficient, A_NFor normalized texture amplitude, λ_NIs the normalized texture wavelength.

9. The system for determining a road surface property based on a road surface texture according to claim 8, wherein the direction feature type determining module specifically includes:

a positive texture determining unit, configured to determine whether the current texture is a positive texture according to the deviation coefficient and the distribution coefficient of the current texture; determining that the current texture is a positive texture if a deviation coefficient of the current texture is greater than a first threshold and a distribution coefficient of the current texture is greater than a second threshold;

a negative texture determining unit, configured to determine whether the current texture is a negative texture according to a deviation coefficient and the distribution coefficient of the current texture when the current texture is not a positive texture; determining that the current texture is a negative texture if a deviation coefficient of the current texture is less than the first threshold and a distribution coefficient of the current texture is less than the second threshold;

a symmetric texture determination unit for determining the current texture as a symmetric texture when the current texture is neither a positive texture nor a negative texture.

10. The system of claim 9, wherein the rough feature type determination module specifically includes:

the judging unit is used for judging whether the rough coefficient of the current texture is larger than a third threshold value or not to obtain a judging result; if the judgment result is yes, a rugged texture determining unit is called; if the judgment result is negative, calling a smooth texture determining unit;

a rugged texture determining unit for determining the current texture as a rugged texture;

and the smooth texture determining unit is used for determining that the current texture is a smooth texture.

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