CN116718132B

CN116718132B - A three-dimensional road surface measurement method and system

Info

Publication number: CN116718132B
Application number: CN202310502212.9A
Authority: CN
Inventors: 张德津; 李清泉; 曹民; 何莉; 徐少波
Original assignee: Shenzhen University
Current assignee: Shenzhen University
Priority date: 2023-05-06
Filing date: 2023-05-06
Publication date: 2024-03-26
Anticipated expiration: 2043-05-06
Also published as: CN116718132A

Abstract

The application relates to the technical field of precision engineering measurement, and provides a pavement three-dimensional measurement method and system, wherein the method comprises the following steps: projecting line laser to a road surface, obtaining a road surface image containing a laser line, correcting gray distribution of the road surface image by using a light intensity distribution model, extracting a laser line center line based on image data corrected by the gray distribution, and obtaining a road surface three-dimensional section point cloud by using an image space and object space calibration relation; establishing a time sequence relation between a measuring camera and a line laser to control working logic of the line laser and the measuring camera; all sensors are integrated into one measuring device, and the three-dimensional pavement point cloud can be directly output according to an external measuring instruction; one or more devices are mounted on the rear of the vehicle to form a measurement system. According to the method, the gray level distribution of the image is corrected through the light intensity distribution model, the accuracy of section measurement and the environmental adaptability are improved, the working life and the safety of the line laser are improved by utilizing time sequence control, and the portability of the device is improved by highly integrating the sensor.

Description

Pavement three-dimensional measurement method and system

Technical Field

The application relates to the technical field of precision engineering measurement, in particular to a pavement three-dimensional measurement method and system.

Background

The road surface technical condition assessment indexes are more and more than 10 kinds of cracks (cracks, pits, hugs and the like), ruts, flatness, abrasion, jumping vehicles and the like, new indexes are continuously proposed along with the improvement of maintenance requirements, the conventional detection technology detects the cracks by using an image method, the ruts are detected by using a section meter, the flatness, the abrasion and the like are detected by using section measurement, different detection equipment systems are formed by integrating the sensors on various types of vehicles, and different indexes adopt different detection technical routes, so that the problems of more sensor types, complex control, difficult expansion, low data processing efficiency and the like are caused. Meanwhile, high-end detection equipment is mainly aimed at high-grade highways, such as highways, national provinces and trunks, and the like, and generally adopts a large-medium bus to integrally measure multiple sensors, and in recent years, the country begins to pay attention to low-grade highway detection, such as rural highways, and because the rural highways have limited traffic conditions, the sensors can only be installed by small-sized vehicles, and because different indexes adopt different routes, a certain difficulty exists in transplanting a measurement system onto a small-sized bearing platform, such as the problems of sensor installation, power supply and the like, and the small-sized vehicles are difficult to solve. Therefore, it is important to research a new road surface measurement method and to unify the detection technical route of multiple indexes of the road surface as much as possible.

The defects such as pavement cracking, rutting, flatness, jumping, abrasion and the like are basically caused by deformation of the pavement, the geometric dimensions of the defects are different from millimeter to decimeter, and if the model can be built by measuring the three-dimensional section point cloud of the pavement with high precision, the extraction of various deformation characteristics of the pavement can be carried out based on the three-dimensional model, so that the technical route of pavement measurement is unified.

The current road surface detection is generally carried out by adopting a mobile vehicle-mounted platform, and all-weather requirements are required to be met. Laser radar, structured light and photogrammetry are three main technologies of high-precision three-dimensional measurement, the laser radar is based on TOF ranging technology, the precision is in a millimeter level, and the phenomenon of inconsistent posture between measurement points in the movement process is measured; the photogrammetry adopts a plurality of cameras, based on stereoscopic vision measurement, one surface or one line is measured each time, the precision is high, but homonymous points required by photogrammetry resolving are difficult to ensure in road surface measurement.

Road surface detection is generally carried out by adopting a mobile vehicle-mounted platform, and all-weather requirements are also required to be met. Laser radar, structured light and photogrammetry are three main technologies of high-precision three-dimensional measurement, the laser radar is based on TOF ranging technology, the precision is in a millimeter level, and the phenomenon of inconsistent posture between measurement points in the movement process is measured; the line structured light is based on the principle of triangulation, a camera and a laser are used for combined measurement, a section is measured each time, the number of the section points is related to the resolution of the adopted camera, the measurement precision can reach sub-millimeter, and the posture of each section is inconsistent during measurement in motion; the photogrammetry adopts a plurality of cameras, based on stereoscopic vision measurement, one surface or one line is measured each time, the precision is high, but homonymous points required by photogrammetry resolving are difficult to ensure in road surface measurement.

The line structure light measurement precision is high, the line structure light sensor is combined with the gesture measurement sensor, the line structure light sensor is suitable for measurement under the high dynamic condition, the three-dimensional measurement of the road surface is carried out by adopting a method of combining a line structure light sensor and an acquisition controller at present, the line structure light sensor is generally composed of a measurement camera, a laser and an internal control circuit, and the acquisition controller is composed of an industrial computer and a synchronous control circuit. And one or more line structure light sensors are used for measuring the road surface as required, each line structure light sensor is arranged at the tail part of the measuring vehicle, and the acquisition controller is arranged in the vehicle.

The measuring camera and the laser are the cores of the three-dimensional measurement of the pavement, the measuring camera and the laser are installed at a certain included angle, the laser is generally perpendicular to the measured surface to project laser rays, the measuring camera and the laser surface form a certain included angle, the measuring camera obtains an image of a laser line area on the measured pavement, a central line of the laser rays in the image is extracted, coordinates (image space coordinates) of the laser rays on the image are obtained, then the actual coordinates of an object space are calculated by combining the image space and the object space calibration relation, and therefore a pavement section is obtained.

Extracting a central line from a laser line imaging image by a camera is a key link of structured light measurement, and depends on the imaging quality of the laser line and the central line extraction precision, the imaging quality can be influenced by the action of natural light on the laser, and the central line extraction precision can be influenced by the inconsistency of pavement textures.

Disclosure of Invention

The embodiment of the application provides a pavement three-dimensional measurement method and system, which are characterized in that the gray level distribution of an image is corrected through a light intensity distribution model, the accuracy and the environmental adaptability of section measurement are improved, the working life and the safety of a line laser are improved by utilizing time sequence control, and the portability of equipment is improved by highly integrating a sensor.

In a first aspect, an embodiment of the present application provides a three-dimensional road surface measurement method, which is applied to a three-dimensional road surface measurement system, where the system includes line structure light three-dimensional measurement devices used on different vehicles, and the number of line structure light three-dimensional measurement devices in the system is one or more; the line structured light three-dimensional measuring device is integrated based on an illuminance sensor, an encoder, a positioning system module, a control module, a measuring camera, a line laser, an attitude sensor and an acquisition and calculation module;

the line structured light three-dimensional measurement device in the road surface three-dimensional measurement system executes a road surface three-dimensional measurement method when detecting a road surface measurement instruction, and the method comprises the following steps:

the line laser emits line laser to the road surface, and the measuring camera acquires a road surface image containing the laser line;

the acquisition and calculation module corrects the gray distribution of the pavement image by using a light intensity distribution model, and extracts a laser line center line based on the image data of the pavement image after the correction of the gray distribution; wherein the light intensity distribution model comprises a correction function of gray scale distribution;

The acquisition and calculation module processes the laser line center line by utilizing the calibration relation of an image space and an object space to obtain a pavement three-dimensional section point cloud;

the road surface three-dimensional broken surface point cloud can be directly output or firstly cached and then output according to system setting;

the pavement image is obtained by exposing and imaging the measurement camera when receiving the gating pulse generated by the control module; the gating pulse is generated by the control module according to the input pulse number of the encoder, the acquisition interval pulse number and the camera exposure parameter; the control module provides delay pulse, and the line laser output is closed after the delay is reached.

In one embodiment, the expression of the light intensity distribution model is as follows:

I'(x)＝I(x)h(x)；

wherein I' (x) represents image data of the road surface image after the gradation distribution correction; i (x) represents a gradation distribution; h (x) represents a correction function of the gradation distribution.

In one embodiment, the correction function of the gray scale distribution is determined based on a correction factor, an area of a left half peak in the gray scale distribution, an area of a right half peak in the gray scale distribution, and a position of an X-axis of each pixel gray scale in the gray scale distribution in a corresponding coordinate system;

The correction function of the gray distribution is as follows:

wherein t represents a correction factor; s is S _l An area representing the left half peak in the gradation distribution; s is S _r An area representing the right half peak in the gradation distribution; x represents the position of the gray scale of each pixel point in the gray scale distribution on the X axis in the corresponding coordinate system;

wherein S is _l And S is equal to _r Is determined by the following formula:

wherein x is _l 、x _r Respectively representing the position of the left half peak width in the corresponding coordinate system and the position of the right half peak width in the corresponding coordinate system in the gray scale distribution, X _m Representing the position of the peak value of the pixel point gray level in the gray level distribution on the X axis in a corresponding coordinate system; i (x) represents a gradation distribution.

In one embodiment, the correction factor is represented by the formula:

wherein W is _a Representing the sum of the left half peak width and the right half peak width in the gray scale distribution, and sigma represents the standard deviation of Gaussian distribution; r represents the center of gravity offset; n represents an index of the correction factor.

In one embodiment, the center of gravity offset is determined based on the following formula:

wherein lw represents the width of the left half peak in the gray scale distribution, and rw represents the width of the right half peak in the gray scale distribution;

the index of the correction factor is determined based on the following formula:

n(r)＝ae ^br +ce ^dr ；

Wherein a is 31370, b is-10.64, c is 1.54, and d is-0.77; r denotes the center of gravity shift amount.

In one embodiment, the extracting the laser line center line based on the image data of the road surface image after the gradation distribution correction includes:

the acquisition and calculation module determines a gray threshold value based on the maximum value of pixel gray in the image data of the pavement image subjected to gray distribution correction;

the acquisition and calculation module determines target pixel gray level from the gray levels of all pixel points of the image data of the pavement image after gray level distribution correction based on the gray level threshold value;

and the acquisition and calculation module extracts a laser line center line based on the gray level of the target pixel point.

In one embodiment, the collecting and calculating module processes the laser line center line to obtain a three-dimensional pavement point cloud by using an image space and object space calibration relation, and the method includes:

the acquisition and calculation module performs data conversion on coordinates of the laser line central line by using an image space and object space calibration relation to obtain a pavement three-dimensional section;

and the acquisition and calculation module corrects the posture of the three-dimensional section of the road surface by utilizing the posture information and generates a three-dimensional section point cloud of the road surface based on the corrected three-dimensional section of the road surface.

The number of the points on the section is related to the horizontal resolution of the measuring camera, the elevation precision is related to the relation of the included angles between the measuring camera and the line laser, and the precision can be better than 0.5 millimeter in road surface measurement.

In one embodiment, before the line laser projects the line laser onto the road surface, the method further comprises:

the control module determines the natural illuminance information of the current environment;

the control module determines the output power of the line laser according to the natural illuminance information of the current environment and by combining the pre-established association relationship among the road illuminance, the image imaging quality and the power of the line laser;

and the control module adjusts the power of the line laser according to the output power of the line laser.

In one embodiment, the sensors are integrated to form a three-dimensional measuring device, and the three-dimensional measuring device inputs the encoder, the GNSS and the upper computer instruction and outputs three-dimensional point cloud data;

the three-dimensional point cloud data is a single three-dimensional section or a collection of a plurality of sections.

The three-dimensional measuring device inputs the instructions of the encoder, the GNSS and the upper computer, outputs three-dimensional data, and the section measuring frequency of the device is related to the measuring range, and can reach more than 10KHz within the 400mm measuring range.

In a second aspect, embodiments of the present application provide a road surface three-dimensional measurement system, including line structured light three-dimensional measurement devices used on different vehicles; one or more line structured light three-dimensional measuring devices are connected with the vehicle through a connecting component arranged on the top of the vehicle; the line structured light three-dimensional measuring device is positioned at a position exceeding the tail part of the vehicle along the backward direction of the vehicle; the line structured light three-dimensional measuring device is integrated based on an illuminance sensor, an encoder, a positioning system module, a control module, a measuring camera, a line laser, an attitude sensor and an acquisition and calculation module; the acquisition and calculation module comprises a processor and a memory storing a computer program, wherein the processor realizes the pavement three-dimensional measurement method according to the first aspect when executing the computer program.

According to the road surface three-dimensional measurement method and system, line laser is projected to a road surface, a road surface image containing a laser line is obtained, gray distribution of the road surface image is corrected by using a light intensity distribution model, a laser line center line is extracted based on image data after the gray distribution correction, and a three-dimensional road surface section point cloud is obtained by using an image space and object space calibration relation; establishing a time sequence relation between a measuring camera and a line laser to control working logic of the line laser and the measuring camera; all sensors are integrated into one measuring device, and the three-dimensional pavement point cloud can be directly output according to an external measuring instruction; one or more devices are mounted on the rear of the vehicle to form a measurement system. According to the method, the gray level distribution of the image is corrected through the light intensity distribution model, the accuracy of section measurement and the environmental adaptability are improved, the working life and the safety of the line laser are improved by utilizing time sequence control, and the portability of the device is improved by highly integrating the sensor.

Drawings

For a clearer description of the present application or of the prior art, the drawings that are used in the description of the embodiments or of the prior art will be briefly described, it being apparent that the drawings in the description below are some embodiments of the present application, and that other drawings may be obtained from these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic flow chart of a pavement three-dimensional measurement method provided in an embodiment of the present application;

fig. 2 is a schematic view of a road surface three-dimensional measurement system according to an embodiment of the present application;

fig. 3 is a schematic view of a scene when the pavement three-dimensional measurement system provided in the embodiment of the present application includes one line structured light three-dimensional measurement device and two line structured light three-dimensional measurement devices;

fig. 4 is a schematic workflow diagram of a three-dimensional measuring device in a pavement three-dimensional measuring system according to an embodiment of the present application;

FIG. 5 is a timing chart of the operational response of a measurement camera and a line laser in a pavement three-dimensional measurement system according to an embodiment of the present application;

fig. 6 is a schematic view of a scene of a line structured light three-dimensional measurement device in a pavement three-dimensional measurement system according to an embodiment of the present application;

Fig. 7 is a schematic diagram of a light intensity distribution model of a laser line section in the pavement three-dimensional measurement method provided in the embodiment of the present application;

FIG. 8 is a schematic view of a three-dimensional cross section of a pavement three-dimensional measurement method according to an embodiment of the present application;

fig. 9 is a schematic diagram of a road surface three-dimensional point cloud in the road surface three-dimensional measurement method provided in the embodiment of the application.

Detailed Description

For the purposes of making the objects, technical solutions and advantages of the present application more apparent, the technical solutions in the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some, but not all, embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.

The pavement three-dimensional measurement method and system provided by the application are described in detail below with reference to examples.

Fig. 1 is a schematic flow chart of a pavement three-dimensional measurement method according to an embodiment of the present application. Referring to fig. 1, in some embodiments, after the process starts, the laser may be controlled so that the line laser is turned on to output, and then the line laser is thrown to the road surface after the power is adjusted, and at the same time, a time delay is output, and after a certain time delay, the laser line reflected by the road surface reaches the moment of the measuring camera, the control module generates a gating pulse, controls the measuring camera to expose and image, and delays for a certain time after the imaging is finished, and the line laser is turned off, so as to complete the acquisition of the section data. The road surface image can be obtained, the three-dimensional section is generated based on the image data obtained by carrying out image gray-scale correction on the road surface image, and the three-dimensional section can be obtained by extracting a laser center line from the image data, then carrying out image space conversion, and carrying out section posture correction on the converted data. And further, judging whether to output the three-dimensional section, if so, outputting the three-dimensional data and ending the flow, and if not, caching and splicing the section.

The pavement three-dimensional measurement method is applied to a pavement three-dimensional measurement system, and when a line structured light three-dimensional measurement device in the pavement three-dimensional measurement system detects a pavement measurement instruction, the pavement three-dimensional measurement method is executed, and the method can comprise the following steps:

step 100, a line laser projects line laser to a road surface, and a measuring camera acquires a road surface image containing the laser line;

fig. 2 is a schematic view of a road surface three-dimensional measurement system according to an embodiment of the present application. As shown in fig. 2, the road surface three-dimensional measurement system in the present application includes a line structured light three-dimensional measurement device that can be used on different vehicles.

The road surface three-dimensional measurement system may include one or more line structured light three-dimensional measurement devices, and one line structured light three-dimensional measurement device may be used on a vehicle to form the road surface three-dimensional measurement system, or a plurality of line structured light three-dimensional measurement devices may be used in combination on the vehicle to form the road surface three-dimensional measurement system.

The line structured light three-dimensional measuring device is connected with the vehicle through a connecting component arranged at the top of the vehicle; the linear structured light three-dimensional measuring device is positioned at a position exceeding the tail part of the vehicle along the backward direction of the vehicle.

Fig. 3 is a schematic view of a road surface three-dimensional measurement system according to an embodiment of the present application, where the road surface three-dimensional measurement system includes one line structured light three-dimensional measurement device and two line structured light three-dimensional measurement devices. As shown in fig. 3, one measuring device (i.e., a line structured light three-dimensional measuring device) or two measuring devices may be provided on the vehicle, and when the measuring device is one, a road surface of a specified road surface width may be covered by one measuring device; in the case of two measuring devices, the road surface of a specified road surface width can be covered by two measuring devices.

All sensors required by the three-dimensional measurement of the pavement can be integrated to form a three-dimensional measurement device. In some embodiments of the present application, each sensor may include a control circuit line laser, an area array camera, an illumination sensor, an IMU (6-axis sensor), an acquisition processing unit, and the like. The three-dimensional measuring device inputs instructions of an encoder, a GNSS and an upper computer, and outputs three-dimensional point cloud data. The three-dimensional point cloud data may be a single three-dimensional cross section or a collection of a plurality of cross sections.

Fig. 4 is a schematic workflow diagram of a three-dimensional measuring device in a pavement three-dimensional measuring system according to an embodiment of the present application. As shown in fig. 4, the three-dimensional measuring device is input with the encoder, the GNSS and the host computer instructions, and the control circuit may send an operation trigger signal to the line laser to control the line laser to project the laser line. The working trigger signal can be sent to the area-array camera to control the area-array camera to expose and image. The acquisition synchronization signal may also be sent to an acquisition processing unit.

Further, the illumination sensor can collect illumination intensity information of the current environment and send illumination intensity signals to the control circuit, so that the control circuit can send power adjustment signals to the line laser according to the illumination intensity signals to control the line laser to carry out power adjustment.

The acquisition processing unit can acquire the acquisition synchronization signals, the road surface images transmitted by the area array camera, the illumination intensity signals transmitted by the illumination sensor, the attitude information transmitted by the IMU, the calibration parameters and the like, process the information and the data, and finally output point cloud.

The line structured light three-dimensional measuring device can be integrated based on an illuminance sensor, an encoder, a positioning system module, a control module, a measuring camera, a line laser, an attitude sensor and an acquisition and calculation module; the acquisition and calculation module comprises a processor and a memory storing a computer program, and the processor realizes the road surface three-dimensional measurement method when executing the computer program.

The positioning system module may be a global navigation satellite system (Global Navigation Satellite System, GNSS) module, which may be hereinafter also referred to as GNSS.

The illuminance sensor can measure the illuminance of natural light and adjust the output power of the line laser by combining illuminance information and imaging relation; the line laser projects laser lines to the pavement, the measuring camera acquires pavement images containing the laser lines, the collecting and calculating module extracts laser line center lines in the pavement images, three-dimensional data are obtained by combining the calibration relation of an image space and an object space, and the three-dimensional data are fused with posture information measured by the posture sensor; the control module calculates mileage according to the output pulse of the encoder and the position output by the GNSS, and obtains a synchronous signal and a trigger signal; the trigger signal drives the measuring camera and the line laser to work, and the synchronous signal establishes a data fusion reference for each measuring sensor.

The illuminance sensor, the encoder and the GNSS are inputs of the control module. The control module calculates the output power of the line laser according to the illuminance information, the image space and the object space calibration relation; calculating the trigger time of the measuring camera and the line laser according to the output of the encoder and the set measuring interval and triggering the measuring camera and the line laser to work; and calculating mileage information according to the GNSS and the encoder to form data synchronous data. In addition, the control module may also power the various sensors and modules.

The acquisition and calculation module acquires data acquired by the measurement camera and the attitude sensor and outputs section data. The acquisition and calculation module processes the image output by the measurement camera, lifts the center line, obtains the section coordinate on the image, and converts the image coordinate into the actual section of the object by combining the calibration relation of the image side and the object side; the attitude information and the section information are matched and correlated by utilizing time and mileage information, and data is provided for future section attitude correction.

The attachment means in this application may be a bracket having an intensity that supports the weight of the line structured light three-dimensional measuring device.

As shown in fig. 2, a power supply may also be provided in the vehicle of the present application to power the line structured light three-dimensional measurement device.

As shown in fig. 2, a data server can be further arranged in the vehicle of the application, and the data server can be connected with the line structured light three-dimensional measurement device through a network port, so that the line structured light three-dimensional measurement device can transmit the obtained road surface three-dimensional section point cloud to the data server through the network port, and road surface technical condition detection is performed through the data server.

As shown in fig. 2, the GNSS and the encoder in the line structured light three-dimensional measurement apparatus may also be disposed on the vehicle and transmit the acquired information to the control module to be used as input of the control module, so as to facilitate better acquisition of corresponding data.

In this application, a road surface on which three-dimensional measurement is required may be specified.

In this application, at non-measurement moment, line laser is in the state of being powered on but does not go out light, measurement camera does not work, the measurement adopts equidistant trigger measurement mode, control module utilizes the encoder to calculate the trigger signal that distance produced line laser and measurement camera, control line laser and measurement camera gate synchronization, realize line laser pulse and measurement camera exposure in the accurate cooperation in time sequence, guarantee line laser project laser line to the road surface and reach the moment of measurement camera after the reflection, control module produces the gating pulse, open the camera shutter, make the camera image, obtain the image that the road surface contains laser line.

The road surface image is obtained by exposing and imaging when the measuring camera receives the gating pulse generated by the control module; the gating pulse is generated by the control module according to the input pulse number of the encoder, the acquisition interval pulse number and the camera exposure parameter, the specific calculation process is not particularly limited, and the gating pulse can be obtained by completing the calculation; the control module provides a delay pulse, and the line laser output is turned off after the delay is reached.

Fig. 5 is a timing chart of working response of a measuring camera and a line laser in the pavement three-dimensional measuring system according to the embodiment of the present application. As shown in fig. 5, the laser outputs an on pulse while providing a delayed pulse, after which the camera is operated and exposed, and after the exposure time, the laser outputs an off pulse.

The control module generates a laser line trigger signal for controlling the line laser to work, the trigger line laser emits laser line to the road surface, and simultaneously the control module provides a delay pulse, and the delay time tau corresponding to the delay pulse is passed ₁ After that, when the laser line reflected by the road surface reaches the measuring camera, the control module generates gating pulse to control the measuring camera to execute a certain exposure time and image, and delay a certain time tau after the imaging is finished ₂ And closing the line laser to finish the acquisition of the data of the primary section.

The pulse width and the delay time are determined according to the response time of the line laser and the exposure time of the measuring camera in the current environment. Assuming that the exposure time of an image shot by a measuring camera is T, the working time of a line laser in the process of acquiring data of one section is T, and the relation between the two is as follows:

t＝τ ₁ +T+τ ₂ 。

fig. 6 is a schematic view of a scene of a line structured light three-dimensional measurement device in a pavement three-dimensional measurement system according to an embodiment of the present application. As shown in fig. 6, the line laser, the measuring camera, the attitude sensor and the illuminance sensor can be fixed on a high-strength bottom plate, so that the sensors are prevented from relative deformation, a certain included angle is kept between the laser and the measuring camera, and the specific angle can be adjusted according to the measurement requirement; the encoder and the GNSS are input to a control circuit board (namely a control module) through external signal lines, and a control circuit in the control module generates trigger control signals and supplies power to each sensor; and the three-dimensional data acquired by the acquisition and calculation module is locally maintained and is output through a network port. In order to facilitate debugging, the line structure light three-dimensional measuring device is externally provided with a VGA, HDMI and other debugging interfaces. The line structured light three-dimensional measuring device is powered by 24V direct current power supply input.

Step 200, the acquisition and calculation module corrects the gray distribution of the pavement image by using the light intensity distribution model, and extracts the laser line center line based on the image data of the pavement image after the gray distribution correction;

after obtaining the road surface image containing the laser lines, the application can acquire the gray distribution of the image.

The gray scale distribution may include gray scale of each pixel point in the image and coordinate information of each pixel point in the image.

Further, the acquisition and calculation module inputs the gray distribution of the road surface image into the light intensity distribution model, and after the light intensity distribution model finishes processing, image data of the road surface image after gray distribution correction output by the light intensity distribution model is obtained, wherein the image data of the road surface image after gray distribution correction can comprise gray distribution correction data. The gradation distribution correction data is data obtained by correcting the gradation distribution.

The method comprises the steps of establishing a light intensity distribution model for the light intensity distribution of the cross section of the laser line, calculating and adjusting the gray level distribution of the cross section deviating from Gaussian distribution, and accurately extracting the center line of the laser line.

Fig. 7 is a schematic diagram of a light intensity distribution model of a laser line section in the pavement three-dimensional measurement method according to the embodiment of the present application. As shown in FIG. 7, the line structure light system is simplified into a planar model, and the object surface P is due to the different reflection characteristics of the measured object surface _k The reflection coefficients of the left and right side areas of the dot are respectively K ₁ 、K ₂ A representation; the included angle between the incidence direction of the laser line and the normal n of the surface of the measured object is alpha, and the included angle between the observation direction of the measuring camera and the incidence direction of the laser line is beta. During measurement, the line laser projects a laser line parallel to the X axis vertically downwards, and the light intensity distribution (gray level distribution in the application) of the laser line is Gaussian curve S ₁ The light intensity distribution after being reflected by the surface of the object is an irregular curve S ₂ 。

Intensity of emitted light I ₀ The mathematical expression of (2) is:

in the above formula, A is the maximum value of light intensity distribution, X _c The center of the ideal light intensity distribution, σ is the standard deviation of the gaussian distribution, and X is the value of the X-axis. According to the Phong reflection model, the reflected light intensity received by the measuring camera from the object surface is ambient light I _e Diffuse reflected light I at the incident light spot _d And specularly reflect light I _s The sum of the three is expressed by a two-dimensional plane model, and the reflected light intensity I (x) is as follows:

I ₁ (x)＝I _a K _a +I ₀ (x)K _d1 cosα+I ₀ (x)K _s1 cos ⁿ (2α-β),x＜X' _k ；

I ₂ (x)＝I _a K _a +I ₀ (x)K _d2 cosα+I ₀ (x)K _s2 cos ⁿ (2α-β),x＞X' _k ；

in the above, I _a For the intensity of the environment, K _a Is the ambient light reflection coefficient; k (K) _d1 And K is equal to _d2 Is P _k Diffuse reflectance, K, of both sides of the dot _s1 And K is equal to _s2 Is P _k Specular reflection coefficients on both sides of the dot; x' _k By the amount of the offset center.

Since the influence of ambient light on the cross-sectional light intensity distribution is limited, ignoring its influence, the reflected light intensity distribution can be written as:

I(x)＝I ₀ (x)[K _d cosα+K _s cos ⁿ (2α-β)]＝I ₀ (x)H(K _d ,K _s ,α,β)；

Wherein H (K) _d ,K _s Alpha, beta) is an attenuation function acting on the original light intensity distribution I ₀ The deformed light intensity distribution is obtained as I (x). Thus, with a known decay function, the original intensity distribution I can be calculated by ₀ (x)：

In actual measurement, H (K _d ,K _s Parameters such as alpha, beta) and the like are all controlledThe spatial positions of the points on the measuring surface are related and cannot be directly calculated. In fact, the end result of the influence of the decay function on the light intensity distribution is to cause the gray-scale center of gravity to shift, and the center line extraction result deviates from the original position.

When the center of gravity shifts, the gray scale on one side is reduced, and the result of the interaction between the original Gaussian distribution and the exponential function can be considered. When the index function is expressed, the gradation distribution having the shift can be corrected, and the corrected gradation distribution result I' (x) can be obtained.

The expression of the light intensity distribution model in the present application may be as follows:

I'(x)＝I(x)h(x)；

wherein I' (x) represents the gradation distribution in the image data of the gradation-distribution-corrected road surface image, specifically the image data of the gradation-distribution-corrected road surface image; i (x) represents a gradation distribution; h (x) represents a correction function of the gradation distribution.

According to the corrected gray level distribution result I' (x), a more accurate center line extraction result can be obtained.

In the present application, the correction function of the gradation distribution is determined based on the correction factor, the area of the left half peak in the gradation distribution, the area of the right half peak in the gradation distribution, and the position of each pixel gradation in the gradation distribution on the X-axis in the corresponding coordinate system.

Specifically, the correction function of the gradation distribution can be as follows:

wherein t represents a correction factor; s is S _l The area of the left half peak in the gray scale distribution; s is S _r The area of the right half peak in the gray scale distribution; x represents the position of each pixel gray in the gray distribution on the X-axis in the corresponding coordinate system.

Wherein S is _l And S is equal to _r Is determined by the following formula:

wherein x is _l 、x _r Respectively representing the position of the left half peak width in the corresponding coordinate system and the position of the right half peak width in the corresponding coordinate system in the gray scale distribution, X _m The position of the peak value of the pixel gray level in the gray level distribution on the X axis in the corresponding coordinate system is represented; i (x) represents a gradation distribution.

Further, the correction factor may be expressed as follows:

wherein W is _a Representing the sum of the left half-peak width and the right half-peak width in the gray scale distribution, and sigma represents the standard deviation of the Gaussian distribution; r represents the center of gravity offset; n represents an index of the correction factor.

The standard deviation of the gaussian distribution can be approximately obtained by the following formula:

Wherein W is _a The sum of the left half-peak width and the right half-peak width in the gradation distribution is represented, and r represents the center of gravity shift amount.

Further, the center of gravity offset is determined based on the following formula:

further, the index of the correction factor is determined based on the following formula:

n(r)＝ae ^br +ce ^dr ；

In the application, gaussian filtering can be used for weakening noise in acquired images, and a sub-pixel interpolation algorithm is used for obtaining peak point position x 'in gray level distribution curve' ₀ . Let a certain column of gray maximum points g ₀ Is x ₀ Definition g ₀ Is adjacent to the upper row of x _-1 Is g _-1 ，g ₀ Next row adjacent position x ₊₁ Is g ₊₁ . To calculate the sub-pixel extremum x' ₀ Defining the offset delta as offset x ₀ Is the distance of (a), namely:

x' ₀ ＝x ₀ +Δ；

let x be ₀ The gray scale distribution around the point is smooth, the offset delta is:

according to g ₀ The width threshold is determined by the size, and the width lw and rw of the left side and the right side are calculated by an interpolation method.

Specifically, the gray value may be g ₀ /e ² The size points serve as boundary points for the width.

Due to g ₀ /e ² The obtained gray value is not necessarily an integer gray value, but the gray image obtained by the measurement camera is an integer gray value of 0 to 255. Distance g ₀ /e ² The upper and lower points with the nearest gray values are established according to the proportional relation to determine g ₀ /e ² The distance between the point and the upper and lower points is g ₀ /e ² The position of the dot is used as the boundary position of the light stripe, and the width is obtained by making a difference between the two positions according to the position of the maximum value.

Further, the gradation correction function h (x) of the column is obtained. According to the experimental result, the gravity center offset r and the index n satisfy the index determination formula of the correction factor.

Therefore, the index n of the correction factor in the corresponding correction function can be determined as long as the gray-scale center-of-gravity offset r of the light bar section is obtained, and the gray-scale distribution is adjusted by using the correction function.

Therefore, the present application can correct the gradation distribution of the road surface image based on the light intensity distribution model.

Specifically, the center point of the gray-scale correction function h (x) can be compared with the maximum point x 'of the gray-scale distribution I (x)' ₀ Aligned and multiplied point by point to obtain a corrected gray scale distribution I' (x).

The correction function is in the form of a continuous exponential function, where the center point of the correction function is the point of the exponential function where x=0, and the point is located at the maximum point position x 'in the gray level distribution curve' ₀ And (3) aligning, and sampling every other unit of the exponential function to obtain a correction value at each pixel of the current column on the light stripe image.

After the gray distribution correction data is obtained, the maximum value of the gray of the pixel point in the image data of the pavement image after the gray distribution correction can be determined, and the gray of the pixel point in each column participating in the calculation of the central point can be determined according to the maximum value of the gray of the pixel point.

Further, center coordinates of all columns are determined based on pixel gray scales of the columns participating in calculation of the center point, and coordinates of a laser line center line and each pixel on the laser line center line in the image are determined based on the center coordinates of the columns.

And 300, processing the center line of the laser line by the acquisition and calculation module by using the calibration relation of the image space and the object space to obtain the three-dimensional pavement point cloud.

After the laser line center line in the road surface image is obtained, the acquisition and calculation module can perform data conversion on the coordinates of the laser line center line according to the calibration relation of the image space and the object space, so as to obtain the three-dimensional section of the road surface at the position on the road surface.

The acquisition and calculation module corrects the three-dimensional section of the road surface by using the posture information acquired by the posture sensor, and generates a road surface three-dimensional section point cloud of the road surface based on the corrected road surface three-dimensional section.

The road surface three-dimensional broken surface point cloud can be directly output or firstly cached and then output according to system setting.

According to the road surface three-dimensional measurement method and system, line laser is projected to a road surface, a road surface image containing a laser line is obtained, gray distribution of the road surface image is corrected by using a light intensity distribution model, a laser line center line is extracted based on image data after gray distribution correction, and a road surface three-dimensional section point cloud is obtained by using an image space and object space calibration relation; establishing a time sequence relation between a measuring camera and a line laser to control working logic of the line laser and the measuring camera; all sensors are integrated into one measuring device, and the three-dimensional pavement point cloud can be directly output according to an external measuring instruction; one or more devices are mounted on the rear of the vehicle to form a measurement system. According to the method, the gray level distribution of the image is corrected through the light intensity distribution model, the accuracy of section measurement and the environmental adaptability are improved, the working life and the safety of the line laser are improved by utilizing time sequence control, and the portability of the device is improved by highly integrating the sensor.

In one embodiment, extracting a laser line center line based on image data of a road surface image after gradation distribution correction includes:

Step 301, a collecting and calculating module determines a gray threshold based on a maximum value of pixel gray in image data of a pavement image after gray distribution correction;

the acquisition and calculation module can acquire the maximum value g 'of the pixel gray level in the image data of the pavement image with the gray level distribution corrected' ₀ The gray value obtained by floating downwards by a certain size is taken as a gray threshold value and is recorded as g _T The specific value of the floating can be set according to actual requirements.

Step 302, the acquisition and calculation module determines the gray level of a target pixel point from the gray level of each pixel point of the image data of the pavement image after the gray level distribution correction based on the gray level threshold;

further, the acquisition and calculation module acquires and calculates that the gray value of each column of pixel points is higher than the gray threshold g _T The gray scale of the pixel point of (2) is taken as the gray scale of the target pixel point to participate in the calculation of the center point.

In step 303, the acquisition and calculation module extracts the laser line center line based on the gray level of the target pixel point.

After obtaining the gray level of each column of the target pixel points, for each column, the acquisition and calculation module can calculate the center coordinate X of each column according to the gray level of each target pixel point of the column and the position of each target pixel point gray level on the X axis in the corresponding coordinate system by combining the following center coordinate calculation formula _c ：

Wherein x is _i The position of the gray scale of each target pixel point on the X axis in the corresponding coordinate system is represented.

Based on this, the center coordinates of all columns can be calculated.

Further, the central coordinates of all the columns are connected to obtain the central line of the laser line, and the coordinates of each pixel point on the central line of the laser line are obtained.

The laser line center line is a measurement section, the number of points on the section is the resolution of the image along the section, and the coordinates of each point are the image coordinates. Fig. 8 is a schematic three-dimensional cross-sectional view of a pavement three-dimensional measurement method according to an embodiment of the present application. In one embodiment, as shown in FIG. 8, the number of points on the section is 2048, where x represents the position on the section and y represents the change in height.

The embodiment can extract the laser line center line based on the image data of the pavement image subjected to gray distribution correction to obtain the laser line center line in the image; and then, according to the laser line central line in the image, the road surface three-dimensional section point cloud with accurate road surface can be generated.

Further, the collecting and calculating module processes the laser line center line by using the calibration relation of the image space and the object space to obtain the three-dimensional pavement point cloud, and the collecting and calculating module comprises the following steps:

step 401, the acquisition and calculation module performs data conversion on coordinates of a laser line central line by using an image space and object space calibration relation to obtain a pavement three-dimensional section;

After the laser line center line in the image is obtained, the acquisition and calculation module can convert the y value corresponding to the coordinate of the laser line center line into the actual height according to the calibration relation of the image space and the object space, so as to obtain the three-dimensional section of the road surface at the position on the road surface. The corresponding relation between the pixel and the actual height can be represented by the calibration relation between the image space and the object space. For example, 1 pixel is 1 mm, 3 mm, 5 mm, or the like, and specifically can be set according to actual conditions.

It should be noted that the above examples are only for understanding the correspondence between the pixels and the actual height, and are not intended to illustrate that 1 pixel in the present application is 1 mm, 3 mm, 5 mm, etc.

Step 402, the acquisition and calculation module corrects the three-dimensional section of the road surface by using the posture information, and generates a three-dimensional section point cloud of the road surface based on the corrected three-dimensional section of the road surface.

After the three-dimensional section of the road surface is obtained, the acquisition and calculation module can also acquire the attitude data acquired by the attitude sensor. Wherein, the gesture information may be a rotation angle along the X-axis.

Therefore, the acquisition and calculation module can correct the three-dimensional section of the road surface through the posture information.

Further, after the posture of the three-dimensional section of the road surface is corrected, a plurality of continuous three-dimensional sections of the road surface after the posture correction is completed can be spliced, and the three-dimensional section point cloud of the road surface is generated. Fig. 9 is a schematic diagram of a road surface three-dimensional point cloud in the road surface three-dimensional measurement method provided by the embodiment of the application, as shown in fig. 9, an x axis in the road surface three-dimensional point cloud schematic diagram is a road surface cross section direction, a y axis is a road driving direction, a z axis is an elevation direction, and after the road surface three-dimensional section is spliced, an integral road surface three-dimensional section point cloud can be obtained.

The number of points on the section is related to the horizontal resolution of the measuring camera, the elevation precision is related to the relation of the included angles between the measuring camera and the line laser, and the precision can be better than 0.5 millimeter in road surface measurement.

The embodiment can process the laser line center line by utilizing the calibration relation of the image space and the object space to generate the pavement three-dimensional section point cloud with accurate pavement.

Before the line laser projects the line laser to the road surface, the method further comprises:

step 1, a control module determines the natural illuminance information of the current environment;

the central line extraction from the line laser line imaging image by the measuring camera is a key link of structured light measurement, the imaging quality of the laser line also has a specific large influence on the central line extraction, and the imaging quality can be influenced by the action of natural light on the laser.

When facing different environmental light sources or the surface characteristics of the measured object, the measured object or the absorption and reflection of the environmental light to the laser line will be different, so that the imaging effect of the light bar is greatly different. Judging whether the power of the laser is proper or not and correspondingly adjusting the power according to the imaging quality of the light bar, wherein the imaging quality of the light bar refers to the relative brightness of the image of the light bar, and calculating through the average normalized pixel gray level of the image. Assuming that the gray value of a certain point in the image with h×w resolution is f (x, y), and the gray value range in the light bar image is 0-255, the relative brightness L is:

where i and j are the row and column sequence numbers, respectively.

Therefore, the control module can acquire the current ambient natural light illuminance information acquired by the illuminance sensor.

Step 2, the control module determines the output power of the line laser according to the natural light illuminance information of the current environment and combining the pre-established association relationship among the road illuminance, the image imaging quality and the power of the line laser;

wherein the line laser is used for emitting laser lines to the road surface;

in this application, the association relationship among the road surface illuminance, the image imaging quality and the line laser power may be established in advance.

According to the method, the relative brightness can be used as a basis for evaluating the imaging quality of the current light bar image, an experiment is designed, illuminance data, image data and a relative brightness range are acquired, the corresponding relation is recorded in a calibration file, and then the output of the laser is regulated according to illuminance information acquired in an actual measurement process.

Therefore, after the illuminance information is obtained, the control module can search the line laser power corresponding to the current environment natural light illuminance information through the association relation among the road surface illuminance, the image imaging quality and the line laser power to obtain the output power of the line laser.

And 3, the control module adjusts the power of the line laser according to the output power of the line laser.

Further, the control module controls the line laser through the obtained output power of the line laser, so that the line laser adjusts the power to the determined output power.

The embodiment can adjust the output power of the line laser according to the current natural light illuminance information, so that an image with high imaging quality can be obtained.

According to the pavement three-dimensional measurement method and system, synchronous control of exposure of a measuring camera and opening and closing time of a line laser is achieved, parameters are calculated through an encoder, a control circuit adopts logic control measurement of opening laser, delaying time, triggering the camera, delaying time and closing laser light emission, the laser does not emit light when the measurement is not carried out, the service life of the laser is prolonged, and the use safety of the laser is guaranteed. The start and stop of the line laser are controlled by utilizing the time sequence, so that the use safety and the service life of the line laser are improved, and meanwhile, the measurement camera is ensured to accurately and clearly shoot the laser line.

Aiming at the problem that the line structure light bar images too bright or too dark due to different ambient lights or measured objects in the actual measurement process, so that the measurement precision of a sensor is reduced, the relation between illuminance and image quality and laser power is established, the output intensity of a laser is dynamically adjusted, the all-weather measurement is better adapted, the image acquisition quality is ensured, and the brightness of a line laser line is controlled to be in a reasonable range in the current environment.

And establishing a light intensity distribution model for the laser line image shot by the measuring camera, integrating the gray distribution according to the gravity center deviation degree of the light bar to judge the gravity center deviation direction, and correspondingly adjusting the gray distribution by the calculated correction function, so that the final light bar center line extraction result moves in the opposite direction of the gravity center deviation, and the influence of the gravity center deviation or gray loss phenomenon caused by the surface change of the measured object on the center line extraction is reduced. And after the gray level distribution of the cross section deviating from Gaussian distribution is calculated and adjusted, the central line of the laser line is accurately extracted, and the three-dimensional measurement accuracy is improved.

The measuring device is integrated, integrates measurement, control and acquisition calculation, can realize measurement work by a single device, is convenient to install and use, and also supports transplantation on different vehicle types. The integrated design makes the system structure simple and clear, avoids complicated connecting wires, is convenient for debug and maintenance, reduces development and maintenance costs, and is convenient for transplanting on different vehicle types.

The barrel outlet power of the line laser can be dynamically adjusted according to the real-time perceived on-site natural light condition so as to adapt to measurement under different illumination, and the center line of the laser line is accurately extracted through the light intensity distribution model of the laser line section, so that the measurement accuracy is improved.

According to the method, the three-dimensional section of the road surface is measured by utilizing line structured light, the influence of the attitude information of the section on the section is corrected, the three-dimensional model is built based on continuous section splicing, the road surface disease detection technology route can be unified, and the measuring sensor and the control are highly integrated, so that future index change is facilitated.

From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and are not limiting thereof; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.

Claims

1. The three-dimensional road surface measuring method is characterized by being applied to a three-dimensional road surface measuring system, wherein the system comprises line structure light three-dimensional measuring devices used on different vehicles, and the number of the line structure light three-dimensional measuring devices in the system is one or more; the line structured light three-dimensional measuring device is integrated based on an illuminance sensor, an encoder, a positioning system module, a control module, a measuring camera, a line laser, an attitude sensor and an acquisition and calculation module;

2. The pavement three-dimensional measurement method according to claim 1, wherein the expression of the light intensity distribution model is as follows:

I'(x)＝I(x)h(x)；

3. The pavement three-dimensional measurement method according to claim 2, wherein the correction function of the gradation distribution is determined based on a correction factor, an area of a left half peak in the gradation distribution, an area of a right half peak in the gradation distribution, and a position of each pixel gradation in the gradation distribution on an X-axis in a corresponding coordinate system;

the correction function of the gray distribution is as follows:

wherein S is _l And S is equal to _r Is determined by the following formula:

4. A pavement three-dimensional measurement method according to claim 3, wherein said correction factor is represented by the formula:

5. The pavement three-dimensional measurement method according to claim 4, wherein the center of gravity offset is determined based on the following formula:

n(r)＝ae ^br +ce ^dr ；

6. The pavement three-dimensional measurement method according to claim 1, wherein the extracting the laser line center line based on the image data of the gradation distribution corrected pavement image comprises:

7. The method according to claim 1, wherein the collecting and calculating module processes the laser line center line to obtain a three-dimensional road surface point cloud by using an image space and object space calibration relation, and the method comprises the steps of:

8. The pavement three-dimensional measurement method according to claim 1, further comprising, before the line laser projects the line laser onto the pavement:

9. The pavement three-dimensional measurement method according to claim 1, wherein the sensors are integrated to form a three-dimensional measurement device, and the three-dimensional measurement device inputs an encoder, a GNSS and an upper computer instruction and outputs three-dimensional point cloud data;

10. The three-dimensional road surface measuring system is characterized by comprising line structured light three-dimensional measuring devices used on different vehicles; one or more line structured light three-dimensional measuring devices are connected with the vehicle through a connecting component arranged on the top of the vehicle; the line structured light three-dimensional measuring device is positioned at a position exceeding the tail part of the vehicle along the backward direction of the vehicle; the line structured light three-dimensional measuring device is integrated based on an illuminance sensor, an encoder, a positioning system module, a control module, a measuring camera, a line laser, an attitude sensor and an acquisition and calculation module; the acquisition and calculation module comprises a processor and a memory storing a computer program, which when executed implements the road surface three-dimensional measurement method according to any one of claims 1 to 9.