A Vehicle-mounted Laser Scanning Data Synchronization Method, Device, Electronic Device and Medium

Abstract

This application relates to the field of data management, and particularly to a method, device, electronic device, and medium for synchronizing on-vehicle lidar scanning data. The method includes: when a pulse instruction is detected, obtaining time tag information and coordinate data, and then determining whether the coordinate data matches preset coordinate data. If the coordinate data does not match the preset coordinate data, analyzing the node information of the coordinate data and the specified node information of the preset coordinate data to generate a data calibration instruction so that the coordinate data matches the preset coordinate data. If the coordinate data matches the preset coordinate data, obtaining system time information, calibrating the time tag information according to the system time information to obtain synchronized time information, determining corresponding working instructions for different devices based on the synchronized time information, and controlling the operation of different devices. This application has the effect of improving the accuracy of data processing.

Description

Technical Field

[0001] This application relates to the field of data processing, and in particular, to a method, device, electronic device, and medium for synchronizing vehicle-mounted laser scanning data. Background Art

[0002] Vehicle-mounted laser scanning technology can obtain urban three-dimensional geographic data with high efficiency, high precision, and low cost, and is one of the most advanced means for obtaining three-dimensional geographic data. The accurate external parameter calibration of a vehicle-mounted laser scanning system is a prerequisite for obtaining high-precision vehicle-mounted laser point clouds.

[0003] Currently, a vehicle-mounted laser scanner integrates a three-dimensional laser scanning device, a GPS positioning module, an inertial measurement device, an odometer, a 360° panoramic digital camera built into the scanner, an assembly control module, and a high-performance board computer and encapsulates them on a vehicle-mounted bracket of an automobile. During the movement of the vehicle, high-precision positioning and attitude data, high-density three-dimensional point clouds, and high-definition continuous panoramic image data are quickly obtained, and time information binding is performed on the collected data according to different clocks in each of the above devices. Through unified georeference and photogrammetric analysis and processing, uncontrolled spatial geographic information data collection and database construction are achieved.

[0004] Regarding the above related technologies, the inventors believe that when using a vehicle-mounted laser scanner to collect spatial geographic information data, due to different clocks in each collection device, asynchronous problems occur when analyzing the data, thereby reducing the accuracy of data processing. Summary of the Invention

[0005] To improve the accuracy of data processing, this application provides a method, device, electronic device, and medium for synchronizing vehicle-mounted laser scanning data.

[0006] In a first aspect, this application provides a method for synchronizing vehicle-mounted laser scanning data, adopting the following technical solution:

[0007] A method for synchronizing vehicle-mounted laser scanning data includes:

[0008] When a pulse command is detected, obtain time tag information and coordinate data, where the time tag information is the data acquisition trigger time of different devices, and the coordinate data is the coordinate data collected by a position acquisition device;

[0009] Determine whether the coordinate data matches preset coordinate data;

[0010] If the coordinate data does not match the preset coordinate data, analyze the node information of the coordinate data and the specified node information of the preset coordinate data to generate a data calibration instruction, which is used to calibrate the coordinate data based on the preset coordinate data so that the coordinate data matches the preset coordinate data;

[0011] If the coordinate data matches the preset coordinate data, obtain the system time information, and calibrate the time tag information according to the system time information to obtain synchronized time information. The system time information is the time information generated by the counting device;

[0012] Determine the working instructions corresponding to different devices based on the synchronized time information, and control the different devices to run.

[0013] In another possible implementation, analyzing the node information of the coordinate data and the specified node information of the preset coordinate data to generate a data calibration instruction includes:

[0014] Determine first node information and second node information based on the node information. The first node information is the coordinate information of the vehicle, and the second node information is the coordinate information of the photographed object;

[0015] Compare the first node information with the specified node information to obtain first comparison result information;

[0016] Compare each node information in the second node information with the specified node information respectively to obtain second comparison result information;

[0017] Judge whether there is preset abnormal information in the first comparison result information and the second comparison result information. If there is preset abnormal information in the first comparison result information and the second comparison result information, determine the abnormal data position information and the calibration data information corresponding to the abnormal data position information according to the first comparison result information and / or the second comparison result information with preset abnormal information;

[0018] Generate a data calibration instruction according to the calibration data information and the initial data information of the abnormal data position information.

[0019] In another possible implementation, after analyzing the node information of the coordinate data and the specified node information of the preset coordinate data to generate a data calibration instruction, it further includes:

[0020] Obtain road surface image information and object image information. The object image information is the object image scanned by the laser scanner;

[0021] Performing image enhancement processing on the road surface image information and the object image information respectively to obtain processed road surface image information and object image information;

[0022] Analyzing the road surface image information to determine whether there is a preset road surface anomaly in the road surface image information, generating road surface prompt information if there is a preset road surface anomaly in the road surface image information, and analyzing the object image information to determine whether there is a preset object anomaly in the object image information if there is no preset road surface anomaly in the road surface image information;

[0023] If the object image information has a preset object anomaly, object anomaly information is generated.

[0024] In another possible implementation, analyzing the road surface image information to determine whether there is a preset road surface anomaly in the road surface image information includes:

[0025] Performing grayscale value processing on the road surface image information to obtain a first grayscale value image;

[0026] Performing binary processing on the first grayscale image to obtain a first binary image;

[0027] Performing image segmentation on the first binary image according to preset requirements to obtain a first segmented image group;

[0028] The segmented images in the first segmented image group are respectively compared with the preset road surface anomaly images to determine whether there is a preset road surface anomaly in the road surface image information.

[0029] In another possible implementation, the generating of road surface prompt information further includes:

[0030] Acquiring vehicle steering information, where the vehicle steering information is steering information within a preset time period after the road surface prompt information is generated;

[0031] Extracting information from the road surface prompt information to obtain prompt turning information;

[0032] It is determined whether the vehicle steering information corresponds to the prompt steering information. If not, the violator information is determined based on the vehicle steering information.

[0033] In another possible implementation, analyzing the object image information to determine whether the object image information contains a preset object anomaly includes:

[0034] Performing grayscale value processing on the object image information to obtain a second grayscale value image;

[0035] Perform binary processing on the second grayscale value image to obtain a second binary image;

[0036] Segment the second binary image according to preset requirements to obtain a second segmentation image group;

[0037] Compare the segmentation images in the second segmentation image group with a preset object abnormal image respectively to determine whether there is a preset object abnormality in the object image information.

[0038] In another possible implementation manner, after determining the information of the violating person based on the vehicle steering information, it further includes:

[0039] Obtain the information of the responsible person, where the information of the responsible person is used to represent the information of the person responsible for driving the vehicle;

[0040] Calculate the proportion of the information of the violating person in the information of the responsible person, and determine whether the proportion exceeds a preset proportion threshold;

[0041] If the proportion exceeds the preset proportion threshold, retrieve the meeting arrangement information and perform occupancy record analysis on the meeting arrangement information to generate meeting information.

[0042] In a second aspect, the present application provides an in-vehicle laser scanning data synchronization device, adopting the following technical solution:

[0043] An in-vehicle laser scanning data synchronization device includes:

[0044] An acquisition module, configured to acquire time tag information and coordinate data when detecting a pulse command, where the time tag information is the data acquisition trigger time of different devices, and the coordinate data is the coordinate data acquired by a position acquisition device;

[0045] A judgment module, configured to judge whether the coordinate data matches preset coordinate data;

[0046] An instruction generation module, configured to analyze the node information of the coordinate data and the specified node information of the preset coordinate data when the coordinate data does not match the preset coordinate data, and generate a data calibration instruction, where the data calibration instruction is used to calibrate the coordinate data based on the preset coordinate data so that the coordinate data matches the preset coordinate data;

[0047] An information calibration module, configured to acquire system time information when the coordinate data matches the preset coordinate data, and perform time information calibration on the time tag information according to the system time information to obtain synchronized time information, where the system time information is the time information generated by a counting device;

[0048] An instruction control module, configured to determine working instructions corresponding to different devices based on the synchronization time information, and control the different devices to operate.

[0049] In a possible implementation manner, when the instruction generation module analyzes the node information of the coordinate data and the specified node information of the preset coordinate data to generate a data calibration instruction, it is specifically configured to:

[0050] Determine first node information and second node information based on the node information, where the first node information is the coordinate information of the vehicle, and the second node information is the coordinate information of the photographed object;

[0051] Compare the first node information with the specified node information to obtain first comparison result information;

[0052] Compare each node information in the second node information with the specified node information respectively to obtain second comparison result information;

[0053] Determine whether there is preset abnormal information in the first comparison result information and the second comparison result information. If there is preset abnormal information in the first comparison result information and the second comparison result information, then determine abnormal data position information and calibration data information corresponding to the abnormal data position information according to the first comparison result information and / or the second comparison result information with the preset abnormal information;

[0054] Generate a data calibration instruction according to the calibration data information and the initial data information of the abnormal data position information.

[0055] In another possible implementation manner, the device further includes: an image acquisition module, an image enhancement module, an image analysis module, and an information generation module, where,

[0056] The image acquisition module is configured to acquire road surface image information and object image information, where the object image information is the object image scanned by a laser scanner;

[0057] The image enhancement module is configured to perform image enhancement processing on the road surface image information and the object image information respectively to obtain processed road surface image information and object image information;

[0058] The image analysis module is configured to analyze the road surface image information to determine whether there is a preset road surface abnormality in the road surface image information. If there is a preset road surface abnormality in the road surface image information, then generate road surface prompt information. If there is no preset road surface abnormality in the road surface image information, then analyze the object image information to determine whether there is a preset object abnormality in the object image information;

[0059] The information generation module is configured to generate object anomaly information if there is a preset object anomaly in the object image information.

[0060] In another possible implementation manner, when the image analysis module analyzes the road surface image information to determine whether there is a preset road surface anomaly in the road surface image information, it is specifically configured to:

[0061] Perform grayscale value processing on the road surface image information to obtain a first grayscale value image;

[0062] Perform binary processing on the first grayscale value image to obtain a first binary image;

[0063] Segment the first binary image according to preset requirements to obtain a first segmentation image group;

[0064] Compare the segmentation images in the first segmentation image group with the preset road surface anomaly images respectively to determine whether there is a preset road surface anomaly in the road surface image information.

[0065] In another possible implementation manner, the device further includes: a steering acquisition module, an information extraction module, and an information judgment module, where

[0066] The steering acquisition module is configured to acquire vehicle steering information, where the vehicle steering information is the steering information within a preset time period after the road surface prompt information is generated;

[0067] The information extraction module is configured to extract information from the road surface prompt information to obtain prompt steering information;

[0068] The information judgment module is configured to judge whether the vehicle steering information corresponds to the prompt steering information. If not, it determines the information of the violating person based on the vehicle steering information.

[0069] In another possible implementation manner, when the image analysis module analyzes the object image information to determine whether there is a preset object anomaly in the object image information, it is specifically configured to:

[0070] Perform grayscale value processing on the object image information to obtain a second grayscale value image;

[0071] Perform binary processing on the second grayscale value image to obtain a second binary image;

[0072] Segment the second binary image according to preset requirements to obtain a second segmentation image group;

[0073] Compare the segmented images in the second segmented image group with the preset object abnormal images respectively to determine whether there is a preset object abnormality in the object image information.

[0074] In another possible implementation manner, the device further includes: a personnel acquisition module, a ratio calculation module, and a meeting generation module, where,

[0075] The personnel acquisition module is configured to acquire the information of the responsible personnel, and the information of the responsible personnel is used to represent the information of the personnel responsible for driving the vehicle;

[0076] The ratio calculation module is configured to calculate the ratio value of the information of the violating personnel in the information of the responsible personnel, and determine whether the ratio value exceeds a preset ratio threshold;

[0077] The meeting generation module is configured to, if the ratio value exceeds the preset ratio threshold, retrieve the meeting arrangement information, and perform occupancy record analysis on the meeting arrangement information to generate meeting information.

[0078] In a third aspect, the present application provides an electronic device, adopting the following technical solution:

[0079] An electronic device, the electronic device includes:

[0080] At least one processor;

[0081] A memory;

[0082] At least one application program, where at least one application program is stored in the memory and is configured to be executed by at least one processor, and the at least one application program is configured to: execute the above vehicle-mounted laser scanning data synchronization method.

[0083] In a fourth aspect, a computer-readable storage medium is provided, and the storage medium stores at least one instruction, at least one program, a code set, or an instruction set, and the at least one instruction, at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the vehicle-mounted laser scanning data synchronization method as shown in any possible implementation manner in the first aspect.

[0084] In summary, the present application includes at least one of the following beneficial technical effects:

[0085] The present application provides a method, apparatus, electronic device and medium for synchronizing vehicle-mounted laser scanning data. Compared with the related art, in the present application, when collecting spatial geographic information data using a vehicle-mounted laser scanner, the electronic device detects a pulse instruction, and then obtains the time tag information of different devices and the coordinate data of the position acquisition device. Then, it determines whether the coordinate data matches the preset coordinate data. When the coordinate data does not match the preset coordinate data, it means that the current coordinate data is abnormal. Therefore, it analyzes the node information of the coordinate data and the specified node information of the preset coordinate data to generate a data calibration instruction, controls and adjusts the coordinate data to make the coordinate data match the preset coordinate data. Then, it obtains the system time information, calibrates the time tag information according to the system time information to obtain the synchronized time information, and then generates corresponding working instructions for different devices according to the synchronized time information to control the operation of different devices, thereby avoiding the occurrence of asynchronous problems when analyzing data due to different clocks in each acquisition device, and further improving the accuracy of data processing. Description of the Drawings

[0086] Figure 1 is a flowchart of a method for synchronizing vehicle-mounted laser scanning data according to an embodiment of the present application;

[0087] Figure 2 is a block diagram of a device for synchronizing vehicle-mounted laser scanning data according to an embodiment of the present application;

[0088] Figure 3 is a schematic diagram of an electronic device according to an embodiment of the present application. Detailed Embodiments

[0089] The following is a further detailed description of the present application in conjunction with the attached Figures 1-3 to further illustrate the present application in detail.

[0090] Those skilled in the art can make modifications to this embodiment without creative contributions according to their needs after reading this specification, but as long as they are within the scope of the claims of the present application, they are protected by the Patent Law.

[0091] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0092] In addition, the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, a vehicle-mounted laser scanning data synchronization method, device, electronic device, and medium and / or B can represent: the independent existence of a vehicle-mounted laser scanning data synchronization method, device, electronic device, and medium, the simultaneous existence of a vehicle-mounted laser scanning data synchronization method, device, electronic device, and medium and B, and the independent existence of B. In addition, the character " / " in this document generally represents an "or" relationship between the preceding and following associated objects unless otherwise specified.

[0093] The following further describes the embodiments of the present application in detail with reference to the accompanying drawings of the specification.

[0094] The embodiments of the present application provide a vehicle-mounted laser scanning data synchronization method, which is executed by an electronic device. The electronic device can be a server or a terminal device. Among them, the server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected through wired or wireless communication methods, and the embodiments of the present application do not limit this, as Figure 1 shown, the method includes:

[0095] Step S10, when a pulse instruction is detected, obtain time tag information and coordinate data.

[0096] Among them, the time tag information is the data acquisition trigger time of different devices, and the coordinate data is the coordinate data collected by the position acquisition device.

[0097] For the embodiments of the present application, the working principle of the adopted laser scanner is as follows: the built-in lidar module emits a laser pulse signal. After being diffusely reflected by the object surface, it is transmitted back to the receiver along almost the same path. The distance between the target point and the scanner can be calculated, and then the lateral scanning angle observation value and the longitudinal scanning angle observation value of each laser pulse are synchronously measured. The coordinates of the target point can be calculated through the above parameters. Therefore, the principle of laser ranging can be used to densely obtain the three-dimensional coordinates, reflectivity, and texture information of the surface of the target object, and perform a true three-dimensional recording of the objects in space.

[0098] Specifically, the staff generates a pulse instruction by triggering the GNSS module switch. After the electronic device detects the pulse instruction, it obtains the coordinate data through the lidar module and obtains the time tag information through the high-stability crystal oscillator module.

[0099] Step S11, determine whether the coordinate data matches the preset coordinate data.

[0100] In an embodiment of the present application, the preset coordinate data is the precise geographical location coordinates of the target object obtained by the GNSS module. Matching the coordinate data obtained by the lidar module with the preset coordinate data achieves the effect of verifying the coordinate data.

[0101] Step S12, if the coordinate data does not match the preset coordinate data, analyze the node information of the coordinate data and the specified node information of the preset coordinate data to generate a data calibration instruction.

[0102] Among them, the data calibration instruction is used to calibrate the coordinate data based on the preset coordinate data so that the coordinate data matches the preset coordinate data.

[0103] Step S13, if the coordinate data matches the preset coordinate data, obtain the system time information, and calibrate the time tag information according to the system time information to obtain the synchronized time information. The system time information is the time information generated by the counting device.

[0104] For the embodiment of the present application, the system time is accurately timed (microsecond level) by a cascaded counter. Thereafter, all input and output signals record the accurate system time; the odometer data (including the current accurate system time) is received in real time through two incremental encoders, one for real-time data recording and the other for calculating the mileage (outputting the camera exposure signal at a fixed distance); the camera exposure can also be controlled by a timer; fixed-time interval exposure is achieved through two cascaded timers; Ports 1 are used to control the synchronous exposure of 7 cameras, and Ports 2 are used to synchronously read the exposure status of 7 cameras. All kinds of input and output data are reflected on the host computer interface.

[0105] Step S14, determine the working instructions corresponding to different devices based on the synchronized time information, and control the different devices to run.

[0106] In an embodiment of the present application, the devices include: a host, a POS module, a panoramic camera module, and a lidar module. The method of controlling different devices to run includes: simultaneously sending the never-trigger information (422 differential) to each different device, and then after the device receives the synchronous trigger signal, sending the corresponding data of different devices to the electronic device. For example: the host sends the current timestamp data, the POS module sends the inertial navigation data, the panoramic camera module sends the panoramic image data, and the lidar module sends the three-dimensional point cloud data.

[0107] For the embodiments of the present application, the time tag information and the coordinate data are both obtained through R232 serial port communication. The time tag information is used to record the system time of each device while recording each device's data, with a baud rate of 38400, and the coordinate data is used to record the coordinate data, with a baud rate of 460802.

[0108] The embodiments of the present application provide a method for synchronizing on-vehicle laser scanning data. When collecting spatial geographic information data using an on-vehicle laser scanner, the electronic device detects a pulse command, and then obtains the time tag information of different devices and the coordinate data of the position acquisition device. Then, it determines whether the coordinate data matches the preset coordinate data. When the coordinate data does not match the preset coordinate data, it indicates that the current coordinate data is abnormal. Therefore, it analyzes the node information of the coordinate data and the specified node information of the preset coordinate data to generate a data calibration command to control and adjust the coordinate data so that the coordinate data matches the preset coordinate data. Then, it obtains the system time information, calibrates the time information of the time tag information according to the system time information to obtain the synchronized time information, and then generates corresponding working commands for different devices according to the synchronized time information to control the operation of different devices, thereby avoiding the occurrence of asynchronous problems when analyzing data due to different clocks in each acquisition device, and further improving the accuracy of data processing.

[0109] A possible implementation manner of the embodiments of the present application is that step S12 specifically includes step S121 (not shown in the figure), step S122 (not shown in the figure), step S123 (not shown in the figure), step S124 (not shown in the figure), and step S125 (not shown in the figure), where

[0110] Step S121, determining the first node information and the second node information based on the node information.

[0111] Among them, the first node information is the coordinate information of the vehicle, and the second node information is the coordinate information of the photographed object.

[0112] Specifically, the number of vehicles in the embodiments of the present application can be multiple or single, and the number of photographed objects can be multiple or single, which is not limited in the embodiments of the present application. The specific number should be determined in combination with the actual working vehicles and the actual application scenarios. For example: there are three vehicles, a, b, and c, which go to different areas to work on laser scanning data. At the same moment, there are trees, stores, and illegally parked vehicles in the area where a is located. Therefore, the second node information corresponding to a is a1, a2, a3, the object to be scanned in the area where b is located includes stores, and the second node information corresponding to b is b1. The object to be scanned in the area where c is located includes scenic spots, and the second node information corresponding to c is c1.

[0113] Step S122: Compare the first node information with the specified node information to obtain the first comparison result information.

[0114] In the embodiment of the present application, the specified node information generally includes the actual position of the vehicle detected by the satellite and the actual position of the photographed object corresponding to the vehicle. For example, if the number of node information is 7, it means that there are seven vehicles on duty currently. Compare the data information in the specified node information with the node information respectively to obtain the first comparison result information. The specific comparison method is as follows: The node information includes a, b, c, d, e respectively. The a node information contains a1, the b node information contains b1 and b2, the c node information contains c1, c2 and c3, the d node information contains d1, d2, d3 and d4, and the e node information contains e1, e2, e3, e4 and e5. The specified node information is the A, B, C, D, E node information. Compare the A node information with the a node information, the B node information with the b node information, the C node information with the c node information, the D node information with the d node information, and the E node information with the e node information respectively, so as to obtain the first comparison result information.

[0115] Step S123: Compare each node information in the second node information with the specified node information respectively to obtain the second comparison result information.

[0116] Specifically, the method for comparing the node information is the same as that in step S122, and will not be elaborated here.

[0117] Step S124: Determine whether there is preset abnormal information in the first comparison result information and the second comparison result information. If there is preset abnormal information in the first comparison result information and the second comparison result information, determine the abnormal data position information and the calibration data information corresponding to the abnormal data position information according to the first comparison result information and / or the second comparison result information with preset abnormal information.

[0118] Step S125: Generate a data calibration instruction according to the calibration data information and the initial data information of the abnormal data position information.

[0119] In a possible implementation manner of the embodiment of the present application, after step S12, it further includes step S21 (not shown in the figure), step S22 (not shown in the figure), step S23 (not shown in the figure) and step S24 (not shown in the figure), where

[0120] Step S21: Obtain the road surface image information and the object image information. The object image information is the object image scanned by the laser scanner.

[0121] In an embodiment of the present application, taking the acquisition of road surface image information and object image information by seven cameras as an example for illustration, including but not limited to seven cameras.

[0122] Specifically, the seven cameras: cameras with seven rotating lenses, where the shooting focal lengths and shooting modes corresponding to each shooting lens are different. For example, some shooting lenses are suitable for shooting at night, and some shooting lenses are suitable for shooting distant objects.

[0123] Step S22: Perform image enhancement processing on the road surface image information and the object image information respectively to obtain the processed road surface image information and object image information.

[0124] For the embodiments of the present application, image enhancement is to enhance the useful information in the image. It can be a distortion process, and its purpose is to improve the visual effect of the image for a given application occasion of the image. Emphasize the overall or local characteristics of the image purposefully, make the original unclear image clear or emphasize certain interesting features, expand the differences between the features of different objects in the image, suppress the uninteresting features, so as to improve the image quality, enrich the information volume, strengthen the image interpretation and recognition effect, and meet the needs of certain special analyses.

[0125] Specifically, image enhancement can be divided into two categories: frequency domain method and spatial domain method. The former regards the image as a two-dimensional signal and performs signal enhancement based on the two-dimensional Fourier transform. By using the low-pass filtering method (i.e., only allowing low-frequency signals to pass), the noise in the image can be removed; by using the high-pass filtering method, high-frequency signals such as edges can be enhanced, making the blurred road surface image information and object image information clear. In the latter spatial domain method, representative algorithms include the local averaging method and the median filtering method (taking the middle pixel value in the local neighborhood), etc., which can be used to remove or weaken the noise.

[0126] Step S23: Analyze the road surface image information to determine whether there is a preset road surface abnormality in the road surface image information. If there is a preset road surface abnormality in the road surface image information, generate road surface prompt information. If there is no preset road surface abnormality in the road surface image information, analyze the object image information to determine whether there is a preset object abnormality in the object image information.

[0127] Step S24: If there is a preset object abnormality in the object image information, generate object abnormality information.

[0128] A possible implementation manner of the embodiment of the present application, step S23 specifically includes step S233 (not shown in the figure), step S234 (not shown in the figure), step S235 (not shown in the figure), and step S236 (not shown in the figure), where

[0129] Step S233: Process the road surface image information to obtain a first grayscale image.

[0130] Specifically, in the field of computers, a grayscale digital image is an image in which each pixel has only one sampled color. Such images are usually displayed as grayscales ranging from darkest black to brightest white. Although theoretically this sampling can be of different shades of any color, or even different colors at different brightness levels. Grayscale images are different from black-and-white images. In the field of computer images, black-and-white images have only two colors, black and white, while grayscale images have many levels of color depth between black and white. However, outside the field of digital images, "black-and-white images" also refer to "grayscale images". For example, grayscale photos are usually called "black-and-white photos".

[0131] In the embodiment of the present application, processing the road surface image information to a grayscale value is actually to avoid stripe distortion.

[0132] Step S234: Perform binary processing on the first grayscale image to obtain a first binary image.

[0133] Specifically, a binary image is an image in which each pixel value has only two possibilities, either black or white. Usually, when converting other images into binary images, a threshold is set. When the value of a certain pixel in the original image is greater than this threshold, we change this pixel to white (color component is 255). If the value of a certain pixel is less than this threshold, we change this pixel to black (color component is 0). After traversing each pixel point of the original image in this way, a binarized image is formed. A binarized image in MATLAB is a two-dimensional pixel matrix, where the first dimension represents the X coordinate of the image and the second dimension represents the Y coordinate of the image.

[0134] Step S235: Segment the first binary image according to preset requirements to obtain a first set of segmented images.

[0135] Specifically, image segmentation is the technology and process of dividing an image into several specific regions with unique properties and extracting the target of interest. It is a key step from image processing to image analysis. The image segmentation methods in the embodiment of the present application include the following several types: threshold-based segmentation methods, region-based segmentation methods, edge-based segmentation methods, and segmentation methods based on specific theories, etc. From a mathematical perspective, image segmentation is the process of dividing a digital image into non-overlapping regions. The process of image segmentation is also a labeling process, that is, pixels belonging to the same region are given the same number, and then the numbered images are collected and combined into a first set of segmented images.

[0136] Step S236: Compare the segmented images in the first segmented image group with the preset road abnormal images respectively to determine whether there is a preset road abnormality in the road image information.

[0137] In a possible implementation manner of the embodiment of the present application, after step S23, steps S331 (not shown in the figure), step 332 (not shown in the figure), and step S333 (not shown in the figure) are further included, where

[0138] Step S331: Obtain vehicle steering information.

[0139] The vehicle steering information is the steering information within a preset time period after the road prompt information is generated.

[0140] In the embodiment of the present application, the preset time period is determined according to the driving speed of the current vehicle and the distance between the abnormal road surface and the vehicle. For example, if the driving speed of the current vehicle is 5 m / minute and the distance between the abnormal road surface and the vehicle is 10 m, then the preset time period is 90 seconds.

[0141] Step S332: Extract information from the road prompt information to obtain prompt steering information.

[0142] Specifically, when an abnormal road surface occurs, the generated road prompt information is information for guiding the driver to avoid the abnormal road surface. For example, when an abnormal road surface appears 5 m directly ahead on the road, check whether there are oncoming vehicles. If not, generate "Please turn left and change lanes to avoid the abnormal road surface 5 m ahead". If so, generate "Please slow down. Wait for the vehicle ahead to pass and then turn left and change lanes to avoid the abnormal road surface 5 m ahead". The prompt conversion information is the steering operation information extracted from the road prompt information, such as: turn left and change lanes.

[0143] Step S333: Determine whether the vehicle steering information corresponds to the prompt steering information. If not, determine the information of the violating person based on the vehicle steering information.

[0144] In a possible implementation manner of the embodiment of the present application, step S23 specifically includes:

[0145] Perform grayscale value processing on the object image information to obtain a second grayscale value image.

[0146] Perform binary processing on the second grayscale value image to obtain a second binary image.

[0147] Segment the second binary image according to preset requirements to obtain a second segmented image group.

[0148] Compare the segmented images in the second segmented image group with the preset object abnormal images respectively to determine whether there is a preset object abnormality in the object image information.

[0149] A possible implementation manner of the embodiment of the present application further includes, after step S333: step Sa (not shown in the figure), step Sb (not shown in the figure), and step Sc (not shown in the figure), where

[0150] Step Sa, obtain the responsible person information.

[0151] The responsible person information is used to represent the information of the person responsible for driving the vehicle.

[0152] Step Sb, calculate the proportion of the information of the violating person in the responsible person information, and determine whether the proportion exceeds the preset proportion threshold.

[0153] Specifically, calculate the number of violating persons in the information of the violating person and the number of responsible persons in the responsible person information, and perform a ratio operation on the number of violating persons and the number of responsible persons to obtain the proportion.

[0154] For the embodiment of the present application, the preset second threshold is 20%.

[0155] Step Sc, if the proportion exceeds the preset proportion threshold, retrieve the meeting arrangement information, and perform occupancy record analysis on the meeting arrangement information to generate meeting information.

[0156] Specifically, the meeting information includes the meeting time, meeting content, and meeting participants

[0157] The above embodiment introduces a vehicle-mounted laser scanning data synchronization method from the perspective of the method flow. The following embodiment introduces a vehicle-mounted laser scanning data synchronization device from the perspective of virtual modules or virtual units. For details, see the following embodiment.

[0158] The embodiment of the present application provides a vehicle-mounted laser scanning data synchronization device, as Figure 2 shown. The vehicle-mounted laser scanning data synchronization device 20 may specifically include: an acquisition module 21, a judgment module 22, an instruction generation module 23, an information calibration module 24, and an instruction control module 25, where

[0159] The acquisition module 21 is used to obtain time tag information and coordinate data when a pulse instruction is detected. The time tag information is the data acquisition trigger time of different devices, and the coordinate data is the coordinate data collected by the position acquisition device;

[0160] The judgment module 22 is used to judge whether the coordinate data matches the preset coordinate data;

[0161] An instruction generation module 23, configured to analyze the node information of the coordinate data and the specified node information of the preset coordinate data when the coordinate data does not match the preset coordinate data, and generate a data calibration instruction, where the data calibration instruction is used to calibrate the coordinate data based on the preset coordinate data so that the coordinate data matches the preset coordinate data;

[0162] An information calibration module 24, configured to obtain system time information when the coordinate data matches the preset coordinate data, and perform time information calibration on the time tag information according to the system time information to obtain synchronized time information, where the system time information is the time information generated by a counting device;

[0163] An instruction control module 25, configured to determine the working instructions corresponding to different devices based on the synchronized time information, and control the different devices to operate.

[0164] In a possible implementation manner of the embodiment of the present application, when the instruction generation module 23 analyzes the node information of the coordinate data and the specified node information of the preset coordinate data to generate a data calibration instruction, it is specifically configured to:

[0165] Determine first node information and second node information based on the node information, where the first node information is the coordinate information of the vehicle, and the second node information is the coordinate information of the photographed object;

[0166] Compare the first node information with the specified node information to obtain first comparison result information;

[0167] Compare each node information in the second node information with the specified node information respectively to obtain second comparison result information;

[0168] Determine whether there is preset abnormal information in the first comparison result information and the second comparison result information. If there is preset abnormal information in the first comparison result information and the second comparison result information, determine the abnormal data position information and the calibration data information corresponding to the abnormal data position information according to the first comparison result information and / or the second comparison result information with preset abnormal information;

[0169] Generate a data calibration instruction according to the calibration data information and the initial data information of the abnormal data position information.

[0170] In another possible implementation manner of the embodiment of the present application, the device 20 further includes: an image acquisition module, an image enhancement module, an image analysis module, and an information generation module, where,

[0171] The image acquisition module is configured to acquire road surface image information and object image information, where the object image information is the object image scanned by a laser scanner;

[0172] An image enhancement module, which is used to perform image enhancement processing on the road surface image information and the object image information respectively to obtain the processed road surface image information and object image information;

[0173] An image analysis module, which is used to analyze the road surface image information to determine whether there is a preset road surface anomaly in the road surface image information. If there is a preset road surface anomaly in the road surface image information, a road surface prompt information is generated. If there is no preset road surface anomaly in the road surface image information, the object image information is analyzed to determine whether there is a preset object anomaly in the object image information;

[0174] An information generation module, which is used to generate object anomaly information if there is a preset object anomaly in the object image information.

[0175] Another possible implementation manner of the embodiment of the present application. When the image analysis module analyzes the road surface image information to determine whether there is a preset road surface anomaly in the road surface image information, it is specifically used for:

[0176] Perform gray value processing on the road surface image information to obtain a first gray value image;

[0177] Perform binary processing on the first gray value image to obtain a first binary image;

[0178] Segment the first binary image according to preset requirements to obtain a first segmentation image group;

[0179] Compare the segmentation images in the first segmentation image group with the preset road surface anomaly images respectively to determine whether there is a preset road surface anomaly in the road surface image information.

[0180] Another possible implementation manner of the embodiment of the present application. The device 20 further includes: a steering acquisition module, an information extraction module, and an information judgment module, where

[0181] The steering acquisition module is used to acquire vehicle steering information, and the vehicle steering information is the steering information within a preset time period after the road surface prompt information is generated;

[0182] The information extraction module is used to extract information from the road surface prompt information to obtain prompt steering information;

[0183] The information judgment module is used to judge whether the vehicle steering information corresponds to the prompt steering information. If not, the information of the violating person is determined based on the vehicle steering information.

[0184] Another possible implementation manner of the embodiment of the present application. When the image analysis module analyzes the object image information to determine whether there is a preset object anomaly in the object image information, it is specifically used for:

[0185] Perform grayscale value processing on the object image information to obtain a second grayscale image;

[0186] Perform binary processing on the second grayscale image to obtain a second binary image;

[0187] Segment the second binary image according to preset requirements to obtain a second segmentation image group;

[0188] Compare the segmentation images in the second segmentation image group with the preset object abnormal images respectively to determine whether there is a preset object abnormality in the object image information.

[0189] Another possible implementation manner of the embodiment of the present application is that the device 20 further includes: a personnel acquisition module, a ratio calculation module, and a meeting generation module, where

[0190] The personnel acquisition module is used to acquire the responsible personnel information, and the responsible personnel information is used to represent the information of the personnel responsible for driving the vehicle;

[0191] The ratio calculation module is used to calculate the ratio value of the violation personnel information in the responsible personnel information and determine whether the ratio value exceeds the preset ratio threshold;

[0192] The meeting generation module is used to, if the ratio value exceeds the preset ratio threshold, retrieve the meeting arrangement information and perform occupancy record analysis on the meeting arrangement information to generate meeting information.

[0193] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated here.

[0194] The embodiment of the present application also introduces an electronic device from the perspective of an entity device, such as Figure 3 as shown, Figure 3 The electronic device 300 shown in the figure includes, in addition to the conventional configuration devices: a processor 301 and a memory 303. Among them, the processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 300 may further include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation to the embodiment of the present application.

[0195] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logical blocks, modules, and circuits described in connection with the disclosure of this application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0196] The bus 302 may include a path for transmitting information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0197] The memory 303 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, or it may also be an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0198] The memory 303 is used to store the application program code for executing the solution of this application, and is controlled by the processor 301 for execution. The processor 301 is used to execute the application program code stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0199] Among them, the electronic device includes but is not limited to: mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The electronic device shown is only an example and should not impose any limitations on the functions and usage scope of the embodiments of this application.

[0200] It should be understood that although the steps in the flowchart of the accompanying drawings are shown in sequence according to the indication of the arrows, these steps do not necessarily need to be executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit and can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages. These sub-steps or stages do not necessarily need to be executed at the same moment, but can be executed at different moments, and their execution order does not necessarily need to be sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0201] The above are only partial implementation manners of this application. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the principle of this application, several improvements and refinements can still be made, and these improvements and refinements should also be regarded as the protection scope of this application.

Claims

1. A vehicle-mounted laser scanning data synchronization method, characterized in that Including: When a pulse instruction is detected, obtain time tag information and coordinate data, where the time tag information is the data acquisition trigger time of different devices, and the coordinate data is the coordinate data collected by a position acquisition device; Determine whether the coordinate data matches preset coordinate data; If the coordinate data does not match the preset coordinate data, analyze the node information of the coordinate data and the specified node information of the preset coordinate data to generate a data calibration instruction, where the data calibration instruction is used to calibrate the coordinate data based on the preset coordinate data so that the coordinate data matches the preset coordinate data; The analyzing the node information of the coordinate data and the specified node information of the preset coordinate data to generate a data calibration instruction includes: Determine first node information and second node information based on the node information, where the first node information is the coordinate information of a vehicle and the second node information is the coordinate information of a photographed object; Compare the first node information and the specified node information to obtain first comparison result information; Compare each node information in the second node information with the specified node information respectively to obtain second comparison result information; Determine whether there is preset abnormal information in the first comparison result information and the second comparison result information. If there is preset abnormal information in the first comparison result information and the second comparison result information, determine abnormal data position information and calibration data information corresponding to the abnormal data position information according to the first comparison result information and / or the second comparison result information with the preset abnormal information; Generate a data calibration instruction according to the calibration data information and the initial data information of the abnormal data position information; If the coordinate data matches the preset coordinate data, obtain system time information and calibrate the time tag information according to the system time information to obtain synchronized time information, where the system time information is the time information generated by a counting device; Determine corresponding working instructions for different devices based on the synchronized time information, and control the different devices to operate.

2. The on-vehicle laser scanning data synchronization method according to claim 1, wherein After the analyzing the node information of the coordinate data and the specified node information of the preset coordinate data to generate a data calibration instruction, it further includes: Obtain road surface image information and object image information, where the object image information is the object image scanned by a laser scanner; Perform image enhancement processing on the road surface image information and the object image information respectively to obtain processed road surface image information and object image information; Analyze the road surface image information to determine whether there is a preset road surface abnormality in the road surface image information. If there is a preset road surface abnormality in the road surface image information, generate road surface prompt information. If there is no preset road surface abnormality in the road surface image information, analyze the object image information to determine whether there is a preset object abnormality in the object image information; If there is a preset object abnormality in the object image information, generate object abnormality information.

3. A vehicle-mounted laser scanning data synchronization method according to claim 2, characterized in that, Analyzing the road surface image information to determine whether there is a preset road surface anomaly in the road surface image information includes: Performing grayscale value processing on the road surface image information to obtain a first grayscale value image; Performing binary processing on the first grayscale value image to obtain a first binary image; Segmenting the first binary image according to preset requirements to obtain a first segmentation image group; Comparing the segmentation images in the first segmentation image group with a preset road surface anomaly image respectively to determine whether there is a preset road surface anomaly in the road surface image information.

4. A vehicle-mounted laser scanning data synchronization method according to claim 2, characterized in that, After generating the road surface prompt information, it further includes: Obtaining vehicle steering information, where the vehicle steering information is the steering information within a preset time period after generating the road surface prompt information; Performing information extraction on the road surface prompt information to obtain prompt steering information; Judging whether the vehicle steering information corresponds to the prompt steering information. If not, determining the information of the violating person based on the vehicle steering information.

5. The method according to claim 2, wherein Analyzing the object image information to determine whether there is a preset object anomaly in the object image information includes: Performing grayscale value processing on the object image information to obtain a second grayscale value image; Performing binary processing on the second grayscale value image to obtain a second binary image; Segmenting the second binary image according to preset requirements to obtain a second segmentation image group; Comparing the segmentation images in the second segmentation image group with a preset object anomaly image respectively to determine whether there is a preset object anomaly in the object image information.

6. The method according to claim 4, characterized in that, After determining the information of the violating person based on the vehicle steering information, it further includes: Obtaining the information of the responsible person, where the information of the responsible person is used to represent the information of the person responsible for driving the vehicle; Calculating the proportion of the information of the violating person in the information of the responsible person and judging whether the proportion exceeds a preset proportion threshold; If the proportion exceeds the preset proportion threshold, retrieving the meeting arrangement information and performing occupancy record analysis on the meeting arrangement information to generate meeting information.

7. A vehicle-mounted laser scanning data synchronization device, characterized in that, It includes: An acquisition module, configured to acquire time tag information and coordinate data when detecting a pulse instruction, where the time tag information is the data acquisition trigger time of different devices, and the coordinate data is the coordinate data collected by a position acquisition device; A judgment module, configured to judge whether the coordinate data matches preset coordinate data; An instruction generation module, configured to analyze the node information of the coordinate data and the specified node information of the preset coordinate data to generate a data calibration instruction when the coordinate data does not match the preset coordinate data, where the data calibration instruction is used to calibrate the coordinate data based on the preset coordinate data so that the coordinate data matches the preset coordinate data; When the instruction generation module analyzes the node information of the coordinate data and the specified node information of the preset coordinate data to generate a data calibration instruction, it is specifically configured to: Determine first node information and second node information based on the node information, where the first node information is the coordinate information of the vehicle, and the second node information is the coordinate information of the photographed object; Compare the first node information and the specified node information to obtain first comparison result information; Compare each piece of node information in the second node information with the specified node information respectively to obtain second comparison result information; Determine whether there is preset abnormal information in the first comparison result information and the second comparison result information. If there is preset abnormal information in the first comparison result information and the second comparison result information, determine the abnormal data position information and the calibration data information corresponding to the abnormal data position information according to the first comparison result information and / or the second comparison result information with preset abnormal information; Generate a data calibration instruction according to the calibration data information and the initial data information of the abnormal data position information; An information calibration module, configured to obtain system time information when the coordinate data matches preset coordinate data, and calibrate the time tag information according to the system time information to obtain synchronized time information, where the system time information is the time information generated by a counting device; An instruction control module, configured to determine working instructions corresponding to different devices based on the synchronized time information, and control the different devices to operate.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; A memory; At least one application program, where at least one application program is stored in the memory and is configured to be executed by at least one processor, and the at least one application program is configured to: execute the vehicle-mounted laser scanning data synchronization method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed on a computer, cause the computer to execute the vehicle-mounted laser scanning data synchronization method according to any one of claims 1 to 6.

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