Vehicle overspeed alarm prompting method and device

Abstract

The invention belongs to the technical field of vehicle speed measurement and intelligent monitoring, and particularly discloses a vehicle overspeed alarm prompting method and device. According to the method, the driving speed of the vehicle is detected by adopting image processing technologies such as adaptive inverse perspective transformation and preprocessing, so that the labeling work of a large amount of data sets is avoided, and the real-time performance of vehicle driving speed detection is improved. The vehicle speed is accurately measured by accurately positioning the license plate area and combining the centroid position of the license plate area, and the accuracy of vehicle running speed detection is improved. According to the invention, when the vehicle is determined to be overspeed, the overspeed warning prompt is given to the vehicle, so that the overspeed vehicle can be intervened in time, and traffic accidents are avoided.

Description

Technical Field

[0001] The present application belongs to the technical field of vehicle speed measurement and intelligent monitoring, and more specifically, to a vehicle speeding alarm prompting method and device. Background Art

[0002] As the roads become flatter and wider, the problem of speeding becomes more and more serious, which seriously threatens people's personal safety. Therefore, it is necessary to adopt effective means to monitor the speed of vehicles in real time to avoid traffic accidents.

[0003] Road video surveillance has the characteristics of simple installation, convenient maintenance, wide monitoring range and good compatibility. Based on this, video detection technology has developed rapidly in the field of vehicle speed detection. At present, there are two main solutions for video-based vehicle speed detection: virtual coil and target tracking-based method. Among them, the virtual coil detects the vehicle speed by setting a virtual coil on the road to replace the real ground induction coil, but this method is limited by the time sampling characteristics of the camera, the speed measurement error is large and the anti-interference ability of this method is poor. The target detection-based method is to calculate the current vehicle speed by calculating the displacement based on the coordinate change of the vehicle feature point calculated by the calibrated camera. With the development of deep learning, there are more and more ways to use neural networks for detection, but this method often requires a large data set, and the balance between real-time and accuracy needs to be improved.

[0004] How to solve the problem of frequent traffic accidents caused by poor real-time and accuracy of vehicle speed measurement is an urgent problem that needs to be solved. Summary of the invention

[0005] In view of the defects of the prior art, the purpose of the present application is to provide a vehicle speeding warning method and device, aiming to solve the problem of frequent traffic accidents caused by poor real-time and accuracy of vehicle speed measurement in the prior art.

[0006] To achieve the above objectives, in a first aspect, the present application provides a vehicle speeding warning method, comprising:

[0007] Obtaining continuous frame images corresponding to the monitoring video of the vehicle;

[0008] Performing adaptive inverse perspective transformation on continuous frame images to obtain a corrected image set;

[0009] Preprocess the images in the rectified image set to obtain the license plate area;

[0010] Based on the centroid of the license plate area, the speed of the vehicle is obtained, and it is determined whether the speed of the vehicle exceeds a first preset value. If so, a speeding alarm is issued to the vehicle.

[0011] In some embodiments, performing adaptive inverse perspective transformation on consecutive frame images to obtain a corrected image set includes:

[0012] According to the pitch angle, tilt angle, vertical field angle, horizontal field angle, width and height of the continuous frame images of the imaging device for collecting the surveillance video, the continuous frame images are adaptively inversely transformed to obtain a corrected image set.

[0013] In some embodiments, preprocessing the images in the rectified image set to obtain the license plate area includes:

[0014] Performing preprocessing including Gaussian filtering, opening and closing operations, and edge detection on the images in the rectified image set to obtain preprocessed images;

[0015] Based on the preprocessed image, the license plate area is obtained.

[0016] In some embodiments, performing preprocessing including Gaussian filtering, opening and closing operations, and edge detection on the images in the rectified image set to obtain the preprocessed images includes:

[0017] Using Gaussian smoothing to remove noise from the image in the corrected image set to obtain a first image;

[0018] The first image is converted into a grayscale image by using a weighted average method, and the opening operation in mathematical morphology processing is used to eliminate the influence of bright spots in the grayscale image to obtain a second image;

[0019] Using the Sobel operator, edge detection is performed on the second image to obtain a gradient amplitude, and pixel points whose gradient amplitude is greater than a second preset value are set as edge points to obtain a third image;

[0020] The third image is processed using an opening operation and a closing operation to fill a closed area surrounded by edge lines formed by edge points, thereby obtaining a preprocessed image.

[0021] In some embodiments, obtaining a license plate region based on the preprocessed image includes:

[0022] Based on the basic information of the vehicle's license plate, the license plate area is filtered out from the preprocessed image.

[0023] In some embodiments, obtaining the speed of the vehicle based on the centroid of the license plate area includes:

[0024] The speed of the vehicle is obtained based on the first centroid, the second centroid and the time interval between adjacent frame images respectively corresponding to the license plate areas in adjacent frame images in the corrected image set.

[0025] In a second aspect, the present application provides a vehicle speeding warning device, comprising:

[0026] A first processing module is used to obtain continuous frame images corresponding to the monitoring video of the vehicle;

[0027] The second processing module is used to perform adaptive inverse perspective transformation on the continuous frame images to obtain a corrected image set;

[0028] The third processing module is used to pre-process the images in the rectified image set to obtain the license plate area;

[0029] The warning prompt module is used to obtain the speed of the vehicle based on the centroid of the license plate area, and determine whether the speed of the vehicle exceeds a first preset value. If so, a speeding warning prompt is issued to the vehicle.

[0030] In a third aspect, the present application provides an electronic device comprising: at least one memory for storing programs; and at least one processor for executing the programs stored in the memory. When the programs stored in the memory are executed, the processor is used to execute the vehicle speeding warning method described in the first aspect or any embodiments of the first aspect.

[0031] In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the vehicle speeding warning method described in the first aspect or any embodiments of the first aspect.

[0032] In a fifth aspect, the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the vehicle speeding warning prompt method described in the first aspect or any embodiments of the first aspect.

[0033] In general, the above technical solutions conceived by this application have the following beneficial effects compared with the prior art:

[0034] The embodiment of the present application provides a vehicle speeding warning method and device, which detects the vehicle's driving speed by using image processing technologies such as adaptive inverse perspective transformation and preprocessing, thereby avoiding the labeling of a large number of data sets and improving the real-time detection of the vehicle's driving speed. By accurately locating the license plate area and accurately measuring the vehicle's speed in combination with the centroid position of the license plate area, the accuracy of the vehicle's driving speed detection is improved. By providing a speeding warning to the vehicle when it is determined that the vehicle is speeding, timely intervention can be achieved on the speeding vehicle to avoid the occurrence of traffic accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1This is one of the flow charts of the vehicle speeding warning method provided in the embodiment of the present application;

[0036] Figure 2 This is the second flow chart of the vehicle speeding warning method provided in the embodiment of the present application;

[0037] Figure 3 It is a structural schematic diagram of a vehicle speeding warning prompt device provided in an embodiment of the present application;

[0038] Figure 4 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0040] The term "and / or" in this article is a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The symbol " / " in this article indicates that the associated objects are in an or relationship, for example, A / B means A or B.

[0041] The terms "first" and "second" in the specification and claims herein are used to distinguish different objects rather than to describe a specific order of the objects. For example, a first preset value and a second preset value are used to distinguish different preset values ​​rather than to describe a specific order of the preset values.

[0042] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0043] In the description of the embodiments of the present application, unless otherwise specified, “plurality” means two or more than two.

[0044] A vehicle speeding warning method provided in an embodiment of the present application uses the center point of the license plate as a feature point and uses an adaptive inverse perspective transformation on the continuous frame images corresponding to the monitoring video. It can calculate the vehicle speed and determine whether it is speeding based on the positional relationship of the feature points in the video frame, thereby realizing intervention in speeding vehicles.

[0045] The embodiments of the present application are described below in conjunction with the drawings in the embodiments of the present application.

[0046] See also Figure 1 , an embodiment of the present application provides a vehicle speeding warning method, which may include: steps 110 to 140.

[0047] Step 110 obtains continuous frame images corresponding to the monitoring video of the vehicle;

[0048] Step 120: performing an adaptive inverse perspective transformation on the continuous frame images to obtain a corrected image set;

[0049] Step 130 pre-processes the images in the rectified image set to obtain a license plate area;

[0050] Step 140 obtains the speed of the vehicle based on the centroid of the license plate area, and determines whether the speed of the vehicle exceeds a first preset value. If so, a speeding alarm is issued to the vehicle.

[0051] In a specific implementation, the monitoring video of the vehicle may be collected by an imaging device, and the imaging device may be a monocular camera, a high-precision camera, or the like.

[0052] By converting the monitoring video of the vehicle collected by the imaging device frame by frame, the corresponding continuous frame images are obtained.

[0053] An adaptive inverse perspective transformation is performed on the images at each frame moment corresponding to the continuous frame images to correct the images at each frame moment, thereby obtaining an image set consisting of the corrected images at each frame moment, that is, a corrected image set.

[0054] The images at each frame moment in the obtained rectified image set are preprocessed including noise removal, region filling and edge recognition, and the license plate region in the preprocessed image is recognized.

[0055] The center position of the license plate area in each preprocessed image is identified and used as the centroid of the license plate area. The displacement of the vehicle at adjacent frame times can be calculated based on the centroid, and the speed of the vehicle can be calculated based on the displacement.

[0056] Determine whether the speed of the vehicle exceeds a first preset value, and if it is determined that the speed of the vehicle exceeds the first preset value, issue an overspeed warning prompt to the vehicle.

[0057] In the embodiment of the present application, the first preset value may be a speed threshold value set according to a speed limit indication on the road on which the vehicle is traveling.

[0058] The embodiment of the present application provides a vehicle speeding warning method, which detects the vehicle's driving speed by using image processing technologies such as adaptive inverse perspective transformation and preprocessing, thereby avoiding the labeling of a large number of data sets and improving the real-time detection of the vehicle's driving speed. By accurately locating the license plate area and accurately measuring the vehicle's speed in combination with the centroid position of the license plate area, the accuracy of the vehicle's driving speed detection is improved. By providing a speeding warning to the vehicle when it is determined that the vehicle is speeding, timely intervention can be achieved on the speeding vehicle to avoid the occurrence of traffic accidents.

[0059] Furthermore, in some embodiments, in step 120, performing adaptive inverse perspective transformation on the continuous frame images to obtain a corrected image set may include:

[0060] According to the pitch angle, tilt angle, vertical field angle, horizontal field angle, width and height of the continuous frame images of the imaging device for collecting the surveillance video, the continuous frame images are adaptively inversely transformed to obtain a corrected image set.

[0061] In the embodiment of the present application, the following adaptive inverse perspective transformation formula is used to perform adaptive inverse perspective transformation on the images at each frame time corresponding to the above continuous frame images to obtain a corrected image set:

[0062]

[0063]

[0064] In the formula, θ p is the pitch angle of the imaging device (such as a monocular camera) used to collect surveillance video, θ0 is the tilt angle of the imaging device, and α r is half of the vertical field of view of the imaging device, α c is half of the horizontal field of view of the imaging device, m is the width of the continuous frame image, n is the height of the continuous frame image, X and Y are the horizontal and vertical coordinates after adaptive inverse perspective transformation, u and v are the horizontal and vertical coordinates of the pixel points in the continuous frame image, and h is the height of the imaging device from the ground.

[0065] A vehicle speeding warning method provided in an embodiment of the present application completes an adaptive inverse perspective transformation of continuous frame images based on internal and external parameters of an imaging device to locate the center of mass of a license plate area, thereby more accurately obtaining the displacement of the vehicle and enabling timely intervention in the monitoring of speeding vehicles.

[0066] Furthermore, in some embodiments, preprocessing the images in the rectified image set to obtain the license plate region in step 130 may include:

[0067] Performing preprocessing including Gaussian filtering, opening and closing operations, and edge detection on the images in the rectified image set to obtain preprocessed images;

[0068] Based on the preprocessed image, the license plate area is obtained.

[0069] In a specific implementation, the noise of the images in the corrected image set is eliminated by performing Gaussian filtering on the images in the corrected image set, the area filling of the noise-eliminated images is achieved by performing opening and closing operations on the noise-eliminated images, and the preprocessing of the images in the corrected image set is completed by performing edge detection on the images after area filling to obtain the preprocessed images.

[0070] Based on the obtained preprocessed image, the license plate area is locked.

[0071] Furthermore, in some embodiments, preprocessing including Gaussian filtering, opening and closing operations, and edge detection is performed on the images in the rectified image set to obtain the preprocessed images, including:

[0072] Using Gaussian smoothing to remove noise from the image in the corrected image set to obtain a first image;

[0073] The first image is converted into a grayscale image by using a weighted average method, and the opening operation in mathematical morphology processing is used to eliminate the influence of bright spots in the grayscale image to obtain a second image;

[0074] Using the Sobel operator, edge detection is performed on the second image to obtain a gradient amplitude, and pixel points whose gradient amplitude is greater than a second preset value are set as edge points to obtain a third image;

[0075] The third image is processed using an opening operation and a closing operation to fill a closed area surrounded by edge lines formed by edge points, thereby obtaining a preprocessed image.

[0076] In the embodiment of the present application, the pre-processed image is obtained by performing noise removal, grayscale conversion, mathematical morphology processing, edge detection and connection on the images in the corrected image set.

[0077] Specifically, noise removal uses Gaussian smoothing, which is calculated based on the distance between each pixel and the center point in the image set after correction. The formula is:

[0078]

[0079] Wherein, g(x,y) is the output value of the Gaussian function, x and y are the horizontal and vertical coordinates of the pixel points in the image in the corrected image set, and σ is the set standard deviation. In the embodiment of the present application, when σ=0.95, the corresponding Gaussian smoothing weight matrix is:

[0080] After the noise of the image in the corrected image set is removed by Gaussian smoothing, the obtained image is the first image, which is a color image.

[0081] Use the weighted average method to convert the first image into a grayscale image. The formula is as follows:

[0082] Gray=0.299*R+0.587*G+0.144*B;

[0083] Wherein, R, G and B are the values ​​of the red, green and blue channels in the first image respectively, and Gray is the calculated grayscale value.

[0084] The opening operation in mathematical morphology processing is used to eliminate the influence of bright spots in the grayscale image, and the obtained image is the second image.

[0085] The Sobel operator is used to perform edge detection on the second image, and its convolution operator template is as follows:

[0086]

[0087]

[0088] In the formula, Δ x f and Δ y f are the horizontal gradient and vertical gradient of the pixel point in the second image respectively, and P is the gradient amplitude.

[0089] The gradient amplitude P is compared with a second preset value, and when the gradient amplitude is greater than the second preset value, the pixel point in the second image is set as an edge point. By traversing each pixel point in the second image, an edge image, i.e., a third image, is obtained.

[0090] The third process is processed using an opening operation and a closing operation, and after the closed area enclosed by the edge lines formed by the above edge points is filled, the image obtained is the pre-processed image.

[0091] In the embodiment of the present application, Gaussian filtering, opening and closing operations, and Sobel operators are comprehensively applied to calculate the vehicle speed in real time and trigger the speeding alarm system by calculating the centroid position of the license plate and its movement distance, thereby realizing vehicle speeding detection more simply and efficiently, with strong adaptability and low deployment cost.

[0092] A vehicle speeding warning method provided in an embodiment of the present application can eliminate the impact of image quality degradation caused by factors such as shooting quality, vehicle speed, and light intensity to a certain extent by preprocessing the images in the corrected image set, thereby improving the positioning accuracy of the license plate area.

[0093] Furthermore, in some embodiments, in the above steps, obtaining the license plate area based on the preprocessed image includes:

[0094] Based on the basic information of the vehicle's license plate, the license plate area is filtered out from the preprocessed image.

[0095] In a specific implementation, the license plate area is roughly located and finely screened according to the basic information of the vehicle license plate to obtain the final license plate area. In the embodiment of the present application, the basic information of the vehicle may specifically include the shape of the license plate (such as the length, width and height of the license plate), the color of the license plate, etc.

[0096] (1) Rough license plate positioning:

[0097] Find all the rectangular areas that may be license plates in the preprocessed image, verify the rectangular areas according to the fixed size and aspect ratio of the license plate, and screen out the candidate areas. Specifically, considering that the aspect ratio of blue and yellow license plates in common motor vehicle license plates is 3.14, and the aspect ratio of green new energy license plates is 3.42, the aspect ratio of the rectangular area of ​​the suspected license plate should be between 2.5-4.5, and the rectangular areas that do not meet the requirements are excluded to obtain the candidate areas.

[0098] (2) Detailed screening of license plates:

[0099] The candidate areas are carefully screened, and the non-license plate areas that do not meet the conditions in the candidate areas are excluded based on the license plate background color (usually yellow, green and blue) to obtain the final license plate area.

[0100] The rough positioning of the license plate mainly considers the shape of the license plate, and locates the rectangular area of ​​the suspected license plate according to the length-width ratio of the license plate; while the precise screening is to judge the color of the suspected area to further screen out the license plate.

[0101] Further, in some embodiments, obtaining the speed of the vehicle based on the centroid of the license plate area in step 140 may include:

[0102] The speed of the vehicle is obtained based on the first centroid, the second centroid and the time interval between adjacent frame images respectively corresponding to the license plate areas in adjacent frame images in the corrected image set.

[0103] In a specific implementation, the centroid of the license plate area of ​​the image in the corrected image set is located, and the centroid position of the license plate area of ​​the previous frame image and the next frame image is directly subtracted and divided by the time interval between the previous and next two frames to calculate the vehicle's driving speed.

[0104] For example, assuming that the centroid coordinates of the license plate area at adjacent frame moments in the continuous frame image are (x1, y1) and (x2, y2), respectively, after the adaptive inverse perspective transformation, (x1, y1) and (x2, y2) are substituted into (u, v) in the above adaptive inverse perspective transformation formula, and the centroid coordinates after the adaptive inverse perspective transformation are (x1′, y1′) and (x2′, y2′), respectively. Assuming that the time interval between adjacent frame moments is t, the speed of the vehicle can be calculated based on the following formula:

[0105]

[0106] Where V is the speed of the vehicle, and s is the displacement of the center of mass of the license plate area of ​​the vehicle at adjacent frame times.

[0107] When the vehicle speed exceeds a first preset value, the vehicle is considered to have exceeded the speed limit, and the alarm of the work area monitoring sounds to give a warning.

[0108] In practical applications, such as Figure 2 As shown, a vehicle speeding warning method provided by an embodiment of the present application includes:

[0109] Step 1: Obtain continuous frame images corresponding to the surveillance video to be detected;

[0110] Step 2: Obtain the corrected image set through adaptive inverse perspective transformation;

[0111] Step 3: performing noise removal, graying, mathematical morphology processing, edge detection and connection on the images in the corrected image set to obtain a preprocessed image;

[0112] Step 4: Locate the license plate area of ​​the preprocessed image;

[0113] Step 5 calculates the speed of the vehicle based on the centroid of the license plate area and determines whether the vehicle is speeding. If so, an alarm will sound in the work area to remind the driver.

[0114] A vehicle speeding warning method provided in an embodiment of the present application determines that the vehicle is speeding when the speed of the vehicle exceeds a preset value, and warns the speeding vehicle by sounding an alarm, thereby improving vehicle driving safety.

[0115] The vehicle overspeed warning prompt device provided by the present application is described below. The vehicle overspeed warning prompt device described below and the vehicle overspeed warning prompt device method described above can be referenced to each other.

[0116] See also Figure 3The embodiment of the present application provides a vehicle speeding warning prompt device, which may include: a first processing module 310 , a second processing module 320 , a third processing module 330 and a warning prompt module 340 .

[0117] The first processing module 310 is used to obtain continuous frame images corresponding to the monitoring video of the vehicle;

[0118] The second processing module 320 is used to perform adaptive inverse perspective transformation on the continuous frame images to obtain a corrected image set;

[0119] The third processing module 330 is used to pre-process the image in the corrected image set to obtain a license plate area;

[0120] The warning prompt module 340 is used to obtain the speed of the vehicle based on the centroid of the license plate area, and determine whether the speed of the vehicle exceeds a first preset value. If so, a speeding warning prompt is issued to the vehicle.

[0121] The vehicle speeding warning device provided in the embodiment of the present application detects the vehicle's driving speed by using image processing technologies such as adaptive inverse perspective transformation and preprocessing, thereby avoiding the labeling of a large number of data sets and improving the real-time detection of the vehicle's driving speed. The vehicle's speed is accurately measured by accurately locating the license plate area and combining the centroid position of the license plate area, thereby improving the accuracy of the vehicle's driving speed detection. By providing a speeding warning to the vehicle when it is determined that the vehicle is speeding, timely intervention can be achieved on the speeding vehicle to avoid the occurrence of traffic accidents.

[0122] It can be understood that the detailed functional implementation of each of the above-mentioned units / modules can be found in the introduction of the aforementioned method embodiment, and will not be repeated here.

[0123] It should be understood that the above-mentioned device is used to execute the method in the above-mentioned embodiment. The implementation principle and technical effect of the corresponding program module in the device are similar to those described in the above-mentioned method. The working process of the device can refer to the corresponding process in the above-mentioned method, which will not be repeated here.

[0124] Based on the method in the above embodiment, the present application embodiment provides an electronic device, see Figure 4 The electronic device may include: a processor (Processor) 410, a communication interface (CommunicationsInterface) 420, a memory (Memory) 430 and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the method in the above embodiment.

[0125] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application.

[0126] Based on the method in the above embodiment, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method in the above embodiment.

[0127] Based on the method in the above embodiment, an embodiment of the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method in the above embodiment.

[0128] It is understandable that the processor in the embodiment of the present application may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0129] The method steps in the embodiments of the present application can be implemented by hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.

[0130] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions may be transmitted from a website site, a computer, a server or a data center to another website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)), etc.

[0131] It should be understood that the various numerical numbers involved in the embodiments of the present application are only used for the convenience of description and are not used to limit the scope of the embodiments of the present application.

[0132] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A vehicle speeding warning method, characterized in that: include: Obtaining continuous frame images corresponding to the monitoring video of the vehicle; Performing an adaptive inverse perspective transformation on the continuous frame images to obtain a corrected image set; Preprocessing the images in the corrected image set to obtain a license plate area; Based on the centroid of the license plate area, the speed of the vehicle is obtained, and it is determined whether the speed of the vehicle exceeds a first preset value. If so, a speeding alarm is issued to the vehicle.

2. The vehicle speeding warning method according to claim 1, characterized in that: The step of performing adaptive inverse perspective transformation on the continuous frame images to obtain a corrected image set includes: According to the pitch angle, tilt angle, vertical field angle, horizontal field angle, and width and height of the continuous frame images of the imaging device that collects the surveillance video, the continuous frame images are adaptively inversely transformed to obtain the corrected image set.

3. The vehicle speeding warning method according to claim 1, characterized in that: The preprocessing of the image in the corrected image set to obtain the license plate area includes: Performing preprocessing including Gaussian filtering, opening and closing operations, and edge detection on the images in the corrected image set to obtain preprocessed images; Based on the preprocessed image, the license plate area is obtained.

4. The vehicle speeding warning method according to claim 3, characterized in that: The preprocessing of the images in the corrected image set including Gaussian filtering, opening and closing operations and edge detection to obtain the preprocessed images includes: Using Gaussian smoothing to remove noise from the images in the corrected image set to obtain a first image; The first image is converted into a grayscale image by using a weighted average method, and an opening operation in mathematical morphology processing is used to eliminate the influence of bright spots in the grayscale image to obtain a second image; Using the Sobel operator, edge detection is performed on the second image to obtain a gradient amplitude, and pixel points whose gradient amplitude is greater than a second preset value are set as edge points to obtain a third image; The third image is processed using an opening operation and a closing operation to fill a closed area surrounded by edge lines formed by edge points to obtain the preprocessed image.

5. The vehicle speeding warning method according to claim 3, characterized in that: The obtaining of the license plate area based on the preprocessed image includes: Based on the basic information of the license plate of the vehicle, the license plate area is screened out from the preprocessed image.

6. The vehicle speeding warning method according to claim 1, characterized in that: The obtaining of the speed of the vehicle based on the centroid of the license plate area includes: The speed of the vehicle is obtained based on the first centroid, the second centroid and the time interval between adjacent frame images respectively corresponding to the license plate areas in adjacent frame images in the corrected image set.

7. A vehicle speeding warning device, characterized in that: include: A first processing module is used to obtain continuous frame images corresponding to the monitoring video of the vehicle; A second processing module is used to perform an adaptive inverse perspective transformation on the continuous frame images to obtain a corrected image set; A third processing module is used to pre-process the images in the corrected image set to obtain a license plate area; The warning prompt module is used to obtain the speed of the vehicle based on the centroid of the license plate area, and determine whether the speed of the vehicle exceeds a first preset value. If so, a speeding warning prompt is issued to the vehicle.

8. An electronic device, characterized in that: include: at least one memory for storing a computer program; At least one processor is used to execute the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the vehicle speeding warning prompt method as described in any one of claims 1-6.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program runs on a processor, the processor executes the vehicle speeding warning prompt method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that When the computer program product runs on a processor, the processor executes the vehicle speeding warning prompt method as described in any one of claims 1 to 6.

Images