Vehicle access gate monitoring system and method based on image matching

Abstract

The invention discloses a vehicle access gate monitoring system and method based on image matching, and belongs to the technical field of image data processing, and the method comprises the steps: collecting the information of a marked vehicle driving into a main lane and the information of a monitored vehicle driving into a target area; the picture of the monitored vehicle is imported into a vehicle model matching model to match the model of the monitored vehicle, and the vehicle acceleration of the corresponding model is obtained; respectively importing the marked vehicle information and the monitored vehicle information into a vehicle passing time estimation strategy to estimate the passing time of the vehicle passing through a channel gate; the passing time of the marked vehicle passing through the channel gate is compared with the passing time of the monitored vehicle passing through the channel gate, and the channel gate is operated according to the comparison result. Through automatic image matching and passing time estimation, the vehicle is monitored in real time, emergency situations are responded in time, manual intervention is reduced, and traffic management is optimized.

Description

Technical Field

[0001] The present invention belongs to the technical field of image data processing, and in particular to a vehicle channel gate monitoring system and method based on image matching. Background Art

[0002] ETC is a dedicated short-range communication between the on-board electronic tag installed on the vehicle windshield and the microwave antenna on the ETC lane at the toll station, using computer networking technology to conduct back-end settlement processing with the bank, so that vehicles can pay highway or bridge fees without stopping at highway or bridge toll stations.

[0003] At present, some car owners try to save high-speed tolls by using other people's ETC information through improper means (such as stopping at the ETC lane barrier machine to secretly observe and wait for an opportunity to cut in line, or driving slowly in the ETC lane, waiting for the ETC vehicle behind to approach and successfully identify it, and then accelerating to pass at the moment the barrier is lifted). The specific scenario diagram is shown below. Figure 3 shown.

[0004] Existing public technologies for preventing ETC card skimming mostly rely on real-time recognition of license plate numbers. They lack the ability to estimate the probability of a vehicle successfully skimming the card based on the vehicle's current speed, vehicle acceleration, and the distance between the vehicle and the gate, and to intercept vehicles that may successfully skim the card.

[0005] For example, a Chinese patent with application publication number CN113724407A discloses an ETC card-swiping identification method, terminal and storage medium. The ETC card-swiping identification method of the invention includes: obtaining the verification information of the target vehicle, and controlling the gate barrier of the ETC system to lift the gate to release the vehicle according to the verification information and the analysis results sent by the server; when the gate barrier is detected to be dropped, obtaining the rear license plate photo of the released vehicle; judging whether the released vehicle has a card-swiping behavior according to the rear license plate photo and the analysis results sent by the server. The invention uses image recognition technology to identify the license plate number of the passing vehicle and compares it with the license plate number sensed by the ETC system, thereby preventing or recording ETC card-swiping behavior.

[0006] For another example, a Chinese patent with application publication number CN114038074A discloses a vehicle traffic control method and system, which is used to reduce the situation where other vehicles cut in line and use ETC to pass, and reduce the time it takes for vehicles to pass. The invention includes: obtaining the first license plate information bound to the ETC card of the vehicle to pass; obtaining the first image of the vehicle to pass on the lane through a first image acquisition device; when the second license plate information identified in the first image matches the first license plate information, controlling the barrier to be in a waiting state; obtaining the second image on the lane through a second image acquisition device within a preset time; determining whether the third license plate information identified in the second image matches the second license plate information, and if not, determining that the vehicle corresponding to the second image is a queue-cutting vehicle using ETC, and controlling the barrier to change from the waiting state to the interception state.

[0007] The above patent has the problem raised by this background technology: the existing public technology lacks the ability to estimate the probability of a vehicle successfully swiping the card based on the vehicle's current speed, vehicle acceleration and the distance between the vehicle and the channel gate, and to intercept vehicles that may successfully swipe the card.

[0008] In order to solve the above problems, the present invention designs a vehicle access gate monitoring system and method based on image matching. Summary of the invention

[0009] In view of the deficiencies in the prior art, the present invention proposes a vehicle gate monitoring system and method based on image matching. The present invention collects information on marked vehicles entering the main lane and information on monitored vehicles entering the target area; imports the image of the monitored vehicle into the vehicle model matching model to match the monitored vehicle model and obtain the vehicle acceleration of the corresponding model; imports the marked vehicle information and the monitored vehicle information into the vehicle travel time estimation strategy respectively to estimate the travel time of the vehicle through the gate; compares the travel time of the marked vehicle through the gate with the travel time of the monitored vehicle through the gate, and operates the gate according to the comparison result. The present invention monitors vehicles in real time and responds to emergencies in a timely manner through automatic image matching and travel time estimation, reduces manual intervention, and optimizes traffic management; the vehicle model matching model can accurately identify the vehicle type, thereby obtaining more accurate vehicle operating parameters, which is helpful to more accurately estimate the travel time; by comparing the travel time of the marked vehicle and the monitored vehicle, and intercepting the vehicle according to the result, the accuracy of vehicle interception management can be ensured.

[0010] To achieve the above object, the present invention provides the following technical solutions: The vehicle gate monitoring method based on image matching includes the following specific steps: S1. Collect information about marked vehicles entering the main lane and monitored vehicles entering the target area; S2, importing the image of the monitored vehicle into the vehicle model matching model to match the monitored vehicle model, and obtaining the vehicle acceleration of the corresponding model; S3, importing the marked vehicle information and the monitored vehicle information into the vehicle travel time estimation strategy to estimate the vehicle's travel time through the channel gate; S4. Compare the passage time of the marked vehicle through the channel gate with the passage time of the monitored vehicle through the channel gate, and operate the channel gate according to the comparison result.

[0011] Specifically, S1 includes the following specific steps: S11, collecting information of the marked vehicle entering the main lane, wherein the marked vehicle information includes the marked vehicle model, the distance between the marked vehicle and the gate, the current speed of the marked vehicle, and the acceleration of the marked vehicle; S12, collecting monitoring vehicle information entering the target area, wherein the monitoring vehicle information includes a monitoring vehicle picture, a monitoring vehicle distance from the gate, and a monitoring vehicle current speed.

[0012] Specifically, S2 includes the following specific steps: S21, importing the image of the monitored vehicle into the vehicle model matching model to match the monitored vehicle model, wherein the vehicle model matching model includes a vehicle model matching calculation formula, and the vehicle model matching calculation formula is: ,in, is the vehicle model matching value, is the pixel point of the vehicle template image, is the pixel value of the vehicle template image, The vehicle target image is at coordinates The pixel value of the corresponding area, is the pixel average of the vehicle template image, The vehicle target image is at coordinates The average pixel value of the corresponding area, is the total number of pixels in the vehicle template image; S22. Obtain the vehicle model corresponding to the highest vehicle model matching value, and obtain the vehicle acceleration according to the corresponding model.

[0013] Specifically, S3 includes the following specific steps: S31. The vehicle travel time estimation strategy includes a vehicle travel time calculation formula, which is: ,in, is the distance between the vehicle and the gate, is the current speed of the vehicle, is the vehicle travel time, is the vehicle acceleration; S32, importing the distance between the marked vehicle and the gate, the current speed of the marked vehicle and the acceleration of the marked vehicle into the vehicle travel time calculation formula to estimate the travel time of the marked vehicle through the channel gate; S33, the distance between the monitored vehicle and the gate, the current speed of the monitored vehicle and the acceleration of the monitored vehicle are introduced into the vehicle travel time calculation formula to estimate the travel time of the monitored vehicle through the channel gate.

[0014] Specifically, S4 includes the following specific steps: Obtain the passage time of the marked vehicle and the passage time of the monitored vehicle through the channel gate. If the passage time of the marked vehicle through the channel gate is less than the passage time of the monitored vehicle through the channel gate, it will pass normally. If the passage time of the marked vehicle through the channel gate is greater than or equal to the passage time of the monitored vehicle through the channel gate, operate the channel gate to intercept the monitored vehicle.

[0015] A vehicle access gate monitoring system based on image matching, which is implemented based on the above-mentioned vehicle access gate monitoring method based on image matching, and includes a control module, an information acquisition module, an information storage module, a vehicle model matching module, a vehicle travel time estimation module and a comparison operation module; Specifically, the control module is used to control the operation of the information collection module, the information storage module, the vehicle model matching module, the vehicle travel time estimation module and the comparison operation module; Specifically, the information collection module is used to collect the information of marked vehicles entering the main lane and the information of monitored vehicles entering the target area, the information storage module is used to store the collected information of marked vehicles entering the main lane and the information of monitored vehicles entering the target area, the vehicle model matching module is used to import the image of the monitored vehicle into the vehicle model matching model to match the monitored vehicle model and obtain the vehicle acceleration of the corresponding model, the vehicle travel time estimation module is used to import the marked vehicle information and the monitored vehicle information into the vehicle travel time estimation strategy respectively to estimate the travel time of the vehicle through the channel gate, and the comparison operation module is used to compare the travel time of the marked vehicle through the channel gate and the travel time of the monitored vehicle through the channel gate, and operate the channel gate according to the comparison result.

[0016] An electronic device includes: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes the above-mentioned vehicle channel gate monitoring method based on image matching by calling the computer program stored in the memory.

[0017] A computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned vehicle access gate monitoring method based on image matching.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention collects information on marked vehicles entering the main lane and information on monitored vehicles entering the target area; imports images of monitored vehicles into a vehicle model matching model to match the model of the monitored vehicle, and obtains the vehicle acceleration of the corresponding model; imports the marked vehicle information and the monitored vehicle information into a vehicle travel time estimation strategy to estimate the travel time of the vehicle through the channel gate; compares the travel time of the marked vehicle through the channel gate with the travel time of the monitored vehicle through the channel gate, and operates the channel gate according to the comparison result. The present invention monitors vehicles in real time and responds to emergencies in a timely manner through automatic image matching and travel time estimation, thereby reducing manual intervention and optimizing traffic management; the vehicle model matching model can accurately identify the vehicle type, thereby obtaining more accurate vehicle operating parameters, which is helpful to more accurately estimate the travel time; by comparing the travel time of the marked vehicle and the monitored vehicle, and intercepting the vehicle according to the result, the accuracy of vehicle interception management can be ensured. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 The present invention is a flow chart of a vehicle access gate monitoring method based on image matching; Figure 2 It is a schematic diagram of the overall framework of the vehicle access gate monitoring system based on image matching of the present invention; Figure 3 A schematic diagram of a scene for monitoring a vehicle access gate according to the present invention. DETAILED DESCRIPTION

[0021] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the present invention will be more comprehensive and complete and fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0022] Example 1 See also Figure 1 The present invention provides an embodiment: a vehicle channel gate monitoring method based on image matching, which includes the following specific steps: S1. Collect information about marked vehicles entering the main lane and monitored vehicles entering the target area; In this embodiment, S1 includes the following specific steps: S11, collecting information about the marked vehicle entering the main lane, the marked vehicle information including the marked vehicle model, the distance between the marked vehicle and the gate, the marked vehicle current speed, and the marked vehicle acceleration; It should be noted that the steps for collecting the marked vehicle model are as follows: Use the license plate recognition system: After the vehicle enters the main channel, the license plate number is recognized by the induction card on the front windshield; Vehicle feature database matching: Match the recognized license plate number with the vehicle feature database to obtain the vehicle model information.

[0023] The steps for collecting the distance between the vehicle and the gate are as follows: Install distance sensors (such as radar, laser or infrared sensors) in the main channel. When a vehicle passes through, the sensor can measure the distance from the vehicle to the gate; The distance data measured by the sensor is transmitted to the information storage module in real time for recording.

[0024] The current speed of the vehicle is collected in the following way: Using radar speed measurement: A radar speed gun is installed in the main channel. When a vehicle passes through the detection area of ​​the radar speed gun, the radar transmits radio waves and receives reflected waves, and the vehicle speed is calculated based on the reflected waves. Use a geomagnetic vehicle detector: Installed under the road surface, when a vehicle passes by, the geomagnetic vehicle detector can calculate the vehicle speed by detecting changes in the magnetic field.

[0025] The vehicle acceleration is collected in the following way: According to the vehicle model information, query the performance indicators provided by the automobile manufacturer in the vehicle's technical specifications, obtain the vehicle's acceleration time per 100 kilometers, and calculate the acceleration according to the acceleration calculation formula Calculate the vehicle's acceleration, where is the final speed of the vehicle, is the initial velocity of the vehicle, is the running time of the vehicle; In the subsequent calculations, the present invention regards the vehicle movement as uniformly accelerated linear motion for the convenience of calculation.

[0026] The data collection of this embodiment can be demonstrated by some codes: def main(): # Initialize the camera and sensors camera = initialize_camera() distance_sensor = initialize_distance_sensor() speed_sensor = initialize_speed_sensor() # Vehicle enters the ETC area vehicle_id = get_vehicle_id() # Get vehicle ID while vehicle_in_etc_area(vehicle_id): # Capture vehicle image vehicle_image = camera.capture_image() # Storing images store_image(vehicle_image, vehicle_id) # Measure the distance between the vehicle and the gate distance_to_gate = distance_sensor.measure_distance(vehicle_id) #Store distance data store_distance(vehicle_id, distance_to_gate) # Measure vehicle speed vehicle_speed = speed_sensor.measure_speed(vehicle_id) #Store speed data store_speed(vehicle_id, vehicle_speed) #Wait or detect that the vehicle has completely passed wait_for_vehicle_to_pass() S12. Collecting information about the monitoring vehicle entering the target area, where the monitoring vehicle information includes a picture of the monitoring vehicle, the distance between the monitoring vehicle and the barrier, and the current speed of the monitoring vehicle.

[0027] It should be noted that the steps for collecting monitoring vehicle images are as follows: Camera installation: Install a high-resolution camera above the gate; Image capture: When a vehicle enters the main channel, the camera automatically captures a photo of the vehicle. A trigger mechanism such as a geomagnetic sensor or an infrared sensor can be used to trigger the photo. Image storage: The captured vehicle images are stored in the information storage module for further analysis and processing.

[0028] It should be noted that after collecting the monitoring vehicle pictures, the pictures are resized, such as changing the size of all pictures to 1242x1660 pixels, to facilitate subsequent image matching.

[0029] See also Figure 3 , the distance between the monitoring vehicle and the gate of the present invention is set to the sum of the length of the two dashed lines; It is necessary to further explain here that Figure 3 The road is divided into a main lane and an auxiliary lane. The main lane is used for marked vehicles, and the auxiliary lane is used for monitoring vehicles. A channel gate is set in front of the main lane, and a camera module is set on the upper left of the channel gate. The camera module is used to take pictures of the vehicle. The shadow area is the target area. When the monitoring vehicle enters the target area, the camera module automatically takes a picture of the monitoring vehicle.

[0030] S2, importing the image of the monitored vehicle into the vehicle model matching model to match the monitored vehicle model, and obtaining the vehicle acceleration of the corresponding model; In this embodiment, S2 includes the following specific steps: S21. Import the image of the monitored vehicle into the vehicle model matching model to match the monitored vehicle model. The vehicle model matching model includes a vehicle model matching calculation formula. The vehicle model matching calculation formula is: ,in, is the vehicle model matching value, is the pixel point of the vehicle template image, is the pixel value of the vehicle template image, The vehicle target image is at coordinates The pixel value of the corresponding area, is the pixel average of the vehicle template image, The vehicle target image is at coordinates The average pixel value of the corresponding area, is the total number of pixels in the vehicle template image; It should be noted here that the method of constructing a rectangular coordinate system is: place the vehicle template image horizontally, take the vertex in the lower left corner as the coordinate origin, take the length of the vehicle template image as the x-axis, and take the width of the vehicle template image as the y-axis to construct a rectangular coordinate system.

[0031] S22. Obtain the vehicle model corresponding to the highest vehicle model matching value, and obtain the vehicle acceleration according to the corresponding model.

[0032] The vehicle model matching model of this embodiment can be displayed by some codes: import cv2 import numpy as np def ncc_matching(template, image): # Convert image to floating point template = np.float32(template) image = np.float32(image) # Get the size of the template and image th, tw = template.shape[:2] ih, iw = image.shape[:2] # Calculate the mean of the template template_mean = np.mean(template) template = template - template_mean # Calculate the mean of each window of the target image image_mean = cv2.boxFilter(image, ddepth=-1, ksize=(tw, th),normalize=True) # Calculate the result of subtracting the mean from each window of the target image image = image - image_mean # Calculate NCC molecules numerator = cv2.filter2D(image, ddepth=-1, kernel=template[::-1,::-1]) # Calculate the NCC denominator template_norm = np.sqrt(np.sum(template**2)) image_norm = np.sqrt(cv2.filter2D(image**2, ddepth=-1, kernel=np.ones((th, tw)))) image_norm[image_norm < 1e-10] = 1e-10 denominator = template_norm * image_norm # Avoid the situation where the denominator is 0 denominator[denominator == 0] = 1e-10 # Calculate NCC value ncc = numerator / denominator # Find the point with the largest NCC value min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(ncc) return max_loc, max_val # Generate test images image = np.random.randint(0, 256, (480, 640), dtype=np.uint8) template = image[200:216, 300:316] # Perform NCC matching location, value = ncc_matching(template, image) # Output matching results print(f"Best match location: {location}, NCC value: {value}") # Draw the matching results on the image result_image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR) cv2.rectangle(result_image, location, (location[0] + template.shape[1], location[1] + template.shape[0]), (0, 255, 0), 2) # Display the result image cv2.imshow("Result", result_image) cv2.waitKey(0) cv2.destroyAllWindows() S3, importing the marked vehicle information and the monitored vehicle information into the vehicle travel time estimation strategy to estimate the vehicle's travel time through the channel gate; In this embodiment, S3 includes the following specific steps: S31. The vehicle travel time estimation strategy includes a vehicle travel time calculation formula, which is: ,in, is the distance between the vehicle and the gate, is the current speed of the vehicle, is the vehicle travel time, is the vehicle acceleration; It should be noted here that the vehicle travel time is obtained by solving a quadratic equation.

[0033] S32, importing the distance between the marked vehicle and the gate, the current speed of the marked vehicle and the acceleration of the marked vehicle into the vehicle travel time calculation formula to estimate the travel time of the marked vehicle through the channel gate; S33, the distance between the monitored vehicle and the gate, the current speed of the monitored vehicle and the acceleration of the monitored vehicle are introduced into the vehicle travel time calculation formula to estimate the travel time of the monitored vehicle through the channel gate.

[0034] S4, comparing the passage time of the marked vehicle passing through the channel gate with the passage time of the monitored vehicle passing through the channel gate, and operating the channel gate according to the comparison result; In this embodiment, S4 includes the following specific steps: Obtain the passage time of the marked vehicle and the passage time of the monitored vehicle through the channel gate. If the passage time of the marked vehicle through the channel gate is less than the passage time of the monitored vehicle through the channel gate, it will pass normally. If the passage time of the marked vehicle through the channel gate is greater than or equal to the passage time of the monitored vehicle through the channel gate, operate the channel gate to intercept the monitored vehicle.

[0035] Example 2 See also Figure 2 , a vehicle access gate monitoring system based on image matching, which is implemented based on the above-mentioned vehicle access gate monitoring method based on image matching, including a control module, an information acquisition module, an information storage module, a vehicle model matching module, a vehicle travel time estimation module and a comparison operation module; In this embodiment, the information collection module is used to collect the marked vehicle information entering the main lane and the monitored vehicle information entering the target area, the information storage module is used to store the collected marked vehicle information entering the main lane and the monitored vehicle information entering the target area, the vehicle model matching module is used to import the image of the monitored vehicle into the vehicle model matching model to match the monitored vehicle model and obtain the vehicle acceleration of the corresponding model, the vehicle travel time estimation module is used to import the marked vehicle information and the monitored vehicle information into the vehicle travel time estimation strategy respectively to estimate the travel time of the vehicle through the channel gate, and the comparison operation module is used to compare the travel time of the marked vehicle through the channel gate and the travel time of the monitored vehicle through the channel gate, and operate the channel gate according to the comparison result.

[0036] In this embodiment, the control module is used to control the operation of the information collection module, the information storage module, the vehicle model matching module, the vehicle travel time estimation module and the comparison operation module.

[0037] Example 3 This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes the above-mentioned vehicle channel gate monitoring method based on image matching by calling the computer program stored in the memory.

[0038] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement the vehicle channel gate monitoring method based on image matching provided by the above method embodiment. The electronic device may also include other components for implementing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface, so as to input and output data. This embodiment will not be described in detail here.

[0039] Example 4 This embodiment provides a computer-readable storage medium storing instructions, which, when a computer program is executed on a computer device, enables the computer device to execute the above-mentioned vehicle access gate monitoring method based on image matching.

[0040] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0041] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0042] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0043] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may 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 or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function according to the embodiment of the present invention 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 from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired network or / and a wireless network. The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media sets. 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. The semiconductor medium may be a solid-state hard disk.

[0044] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0045] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0046] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of units is only one way. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces. The indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0047] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed on multiple network units, and some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0048] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0049] In the description of this specification, the descriptions with reference to the terms "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example, and the specific features, structures, materials or characteristics described may be combined in an appropriate manner in any one or more embodiments or examples.

[0050] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can well understand and use the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A vehicle gate monitoring method based on image matching, characterized in that: The specific steps include: S1. Collect information about marked vehicles entering the main lane and monitored vehicles entering the target area; S2, importing the image of the monitored vehicle into the vehicle model matching model to match the monitored vehicle model, and obtaining the vehicle acceleration of the corresponding model; S3, importing the marked vehicle information and the monitored vehicle information into the vehicle travel time estimation strategy to estimate the vehicle's travel time through the channel gate; S4. Compare the passage time of the marked vehicle through the channel gate with the passage time of the monitored vehicle through the channel gate, and operate the channel gate according to the comparison result.

2. The vehicle gate monitoring method based on image matching according to claim 1, characterized in that: The S2 comprises the following specific steps: S21, importing the image of the monitored vehicle into the vehicle model matching model to match the monitored vehicle model, wherein the vehicle model matching model includes a vehicle model matching calculation formula, and the vehicle model matching calculation formula is: ,in, is the vehicle model matching value, is the pixel point of the vehicle template image, is the pixel value of the vehicle template image, The vehicle target image is at coordinates The pixel value of the corresponding area, is the pixel average of the vehicle template image, The vehicle target image is at coordinates The average pixel value of the corresponding area, is the total number of pixels in the vehicle template image; S22. Obtain the vehicle model corresponding to the highest vehicle model matching value, and obtain the vehicle acceleration according to the corresponding model.

3. The vehicle gate monitoring method based on image matching as claimed in claim 2, characterized in that: The S3 comprises the following specific steps: S31. The vehicle travel time estimation strategy includes a vehicle travel time calculation formula, which is: ,in, is the distance between the vehicle and the gate, is the current speed of the vehicle, is the vehicle travel time, is the vehicle acceleration; S32, importing the distance between the marked vehicle and the gate, the current speed of the marked vehicle and the acceleration of the marked vehicle into the vehicle travel time calculation formula to estimate the travel time of the marked vehicle through the channel gate; S33, the distance between the monitored vehicle and the gate, the current speed of the monitored vehicle and the acceleration of the monitored vehicle are introduced into the vehicle travel time calculation formula to estimate the travel time of the monitored vehicle through the channel gate.

4. The vehicle gate monitoring method based on image matching as claimed in claim 3, characterized in that: The S4 comprises the following specific steps: Obtain the passage time of the marked vehicle and the passage time of the monitored vehicle through the channel gate. If the passage time of the marked vehicle through the channel gate is less than the passage time of the monitored vehicle through the channel gate, it will pass normally. If the passage time of the marked vehicle through the channel gate is greater than or equal to the passage time of the monitored vehicle through the channel gate, operate the channel gate to intercept the monitored vehicle.

5. The vehicle gate monitoring method based on image matching as claimed in claim 4, characterized in that: The S1 comprises the following specific steps: S11, collecting information of the marked vehicle entering the main lane, wherein the marked vehicle information includes the marked vehicle model, the distance between the marked vehicle and the gate, the current speed of the marked vehicle, and the acceleration of the marked vehicle; S12, collecting monitoring vehicle information entering the target area, wherein the monitoring vehicle information includes a monitoring vehicle picture, a monitoring vehicle distance from the gate, and a monitoring vehicle current speed.

6. A vehicle access gate monitoring system based on image matching, which is implemented based on the vehicle access gate monitoring method based on image matching as claimed in any one of claims 1 to 5, characterized in that: It includes a control module, an information collection module, an information storage module, a vehicle model matching module, a vehicle travel time estimation module and a comparison operation module. The control module is used to control the operation of the information collection module, the information storage module, the vehicle model matching module, the vehicle travel time estimation module and the comparison operation module.

7. The vehicle gate monitoring system based on image matching as claimed in claim 6, characterized in that: The information collection module is used to collect the marked vehicle information entering the main lane and the monitored vehicle information entering the target area, the information storage module is used to store the collected marked vehicle information entering the main lane and the monitored vehicle information entering the target area, the vehicle model matching module is used to import the image of the monitored vehicle into the vehicle model matching model to match the monitored vehicle model and obtain the vehicle acceleration of the corresponding model, the vehicle travel time estimation module is used to import the marked vehicle information and the monitored vehicle information into the vehicle travel time estimation strategy respectively to estimate the travel time of the vehicle through the channel gate, and the comparison operation module is used to compare the travel time of the marked vehicle through the channel gate and the travel time of the monitored vehicle through the channel gate, and operate the channel gate according to the comparison result.

8. An electronic device, characterized in that: include: A memory and a processor, wherein the memory stores a computer program that can be called by the processor, and the processor executes the vehicle channel gate monitoring method based on image matching as described in any one of claims 1 to 5 by calling the computer program stored in the memory.

9. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer executes the vehicle access gate monitoring method based on image matching as described in any one of claims 1-5.

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