An electronic toll collection system based on high-precision recognition

Abstract

The present invention relates to the technical field of electronic non-stop toll collection, and in particular to an electronic non-stop toll collection system based on high-precision identification, including a data acquisition module, an information processing module, and an identification and deduction module. The present invention greatly improves the accuracy of license plate recognition and the reliability of the system through advanced data acquisition and processing technology. The system collects license plate images through image sensors in the environmental monitoring area, and uses character recognition and judgment units for high-precision recognition to ensure that a high recognition rate can be maintained even under adverse weather conditions. By real-time monitoring of vehicle speed and image clarity, the system can dynamically adjust the heating temperature to prevent image blur and equipment failure. The system automatically adjusts system parameters for interfering weather such as rain and snow, thereby improving the stability of license plate recognition under various climatic conditions. It effectively solves the problem of low accuracy of license plate information recognition under extreme weather conditions due to reliance on light sources and light sensors.

Description

Technical Field

[0001] The invention relates to the technical field of electronic non-stop toll collection, and in particular to an electronic non-stop toll collection system based on high-precision identification. Background Art

[0002] With the frequent occurrence of extreme weather events such as heavy rain, blizzards and dense fog, the performance of traditional electronic toll collection systems in these harsh environments is significantly limited. Extreme weather conditions often lead to problems such as insufficient light, blurred images, sensor interference, etc., which reduce the accuracy of license plate recognition and increase the risk of misidentification and missed recognition. This not only affects the accuracy of charging, but may also cause vehicle congestion and toll delays, damaging the user experience.

[0003] The patent document with publication number CN105488856A discloses a non-stop electronic toll collection system based on optical signals. The system includes: a pressure-bearing plate, which is arranged in the passage of the vehicle, and the pressure-bearing plate is movably connected to the ground and covers the lateral area of ​​the passage; a pressure switch, which is arranged below the pressure-bearing plate; an LED light source, which is connected to the pressure switch, and the pressure switch controls the switch of the LED light source; a light sensor, which is arranged in the same closed space as the LED light source; a processor, which is connected to the light sensor, and the processor is also connected to a deduction device; a motor, which is connected to the processor and is used to receive the on and off signals of the processor to start or stop; and a lifting barrier, which is connected to the motor.

[0004] It can be seen that the system mainly relies on LED light sources and optical sensors for license plate recognition, which may be affected by ambient light and weather conditions (such as rain, snow, and fog), resulting in reduced recognition accuracy. The recognition accuracy is not as high as that of the image processing algorithm when using light signals for recognition, and it depends on the working status of the optical sensor and LED light source. There is a recognition lag problem in high-speed vehicles. When the environment or vehicle conditions change, the system cannot adjust the recognition parameters in time. Summary of the invention

[0005] To this end, the present invention provides an electronic toll collection system based on high-precision recognition, so as to overcome the problem in the prior art of low accuracy of license plate information recognition under extreme weather conditions due to reliance on light sources and light sensors.

[0006] To achieve the above object, the present invention provides an electronic toll collection system based on high-precision recognition, comprising:

[0007] A data acquisition module, comprising an image sensor for acquiring real-time license plate images of each vehicle in the monitoring area, a weather sensor for acquiring real-time weather information in the monitoring area, and a vehicle speed sensor for acquiring real-time vehicle speeds of each vehicle in the monitoring area, wherein the monitoring area comprises an environment monitoring area, a vehicle speed monitoring area, and a toll deduction area, and the length of the environment monitoring area is a preset monitoring distance;

[0008] The data acquisition module further includes a heating unit disposed near the image sensor;

[0009] An information processing module is connected to the data acquisition module, and includes a character recognition and determination unit and an environment determination unit. The character recognition and determination unit is used to recognize the license plate characters of the real-time license plate image collected by the image sensor in the environmental monitoring area, and to make a determination according to the number of license plate characters and a preset standard character ratio; the environment determination unit is used to make a determination according to the determination result of the character recognition and determination unit, the real-time weather information collected by the weather sensor and the preset interference weather information, and to operate the heating unit at a preset heating temperature according to the determination result;

[0010] The information processing module further includes a clarity recognition and determination unit and an environment correction unit. The clarity recognition and determination unit is used to recognize the clarity of the real-time license plate image collected by the image sensor in the vehicle speed monitoring area, and make a determination based on the clarity, the real-time vehicle speed collected by the vehicle speed sensor in the vehicle speed monitoring area, and a preset standard matching degree; the environment correction unit is used to correct the heating temperature based on the determination result of the clarity recognition and determination unit and the standard matching degree, and operate the heating unit at the corrected heating temperature;

[0011] The identification and deduction module is connected to the information processing module and the data acquisition module respectively, and is used to identify the license plate characters of the real-time license plate image collected by the image sensor in the deduction area, make a judgment based on the number of license plate characters and a preset standard duration, and store the video of the vehicle passing through the monitoring area and adjust the monitoring distance based on the judgment result, or enter the license plate characters and make a deduction, or issue a maintenance reminder.

[0012] Furthermore, the character recognition determination unit determines according to the number of license plate characters and a preset standard character ratio, including:

[0013] The character recognition determination unit is provided with a standard total number of characters, and the ratio of the number of license plate characters to the standard total number of characters is calculated to obtain a character recognition ratio. When the character recognition ratio is less than the standard character ratio, the environment determination unit is enabled.

[0014] Further, the environment determination unit makes a determination according to the determination result of the character recognition determination unit according to the real-time weather information collected by the weather sensor and the preset interference weather information, including:

[0015] When the character recognition determination unit determines to enable the environment determination unit, the environment determination unit determines that the image sensor needs to be heated when the real-time weather information collected by the weather sensor is interference weather information.

[0016] Furthermore, the definition recognition and determination unit recognizes the definition of the real-time license plate image collected by the image sensor in the vehicle speed monitoring area, including:

[0017] The clarity recognition and determination unit uses an image processing algorithm to recognize the clarity of the real-time license plate image, and standardizes the clarity of the real-time license plate image according to a preset standard clarity to obtain a clarity score.

[0018] Furthermore, a standard vehicle speed is set in the clarity recognition and judgment unit, and the absolute value of the difference between the real-time vehicle speed collected in the speed monitoring area and the standard vehicle speed is calculated, the ratio of the absolute value to the standard vehicle speed is calculated, and the difference between 1 and the ratio is calculated to obtain the vehicle speed score.

[0019] Furthermore, the clarity recognition and judgment unit is provided with a clarity weight and a vehicle speed weight, and the product of the clarity weight and the clarity score, the product of the vehicle speed weight and the vehicle speed score, and the sum of the product of the clarity weight and the clarity score and the product of the vehicle speed weight and the vehicle speed score are calculated to obtain the matching degree.

[0020] Furthermore, the clarity recognition and determination unit determines that the heating temperature needs to be corrected when the matching degree is less than a standard matching degree.

[0021] Furthermore, when the clarity recognition and determination unit determines that the heating temperature needs to be corrected, the environment correction unit increases the corrected heating temperature according to the standard matching degree correction heating temperature, the matching degree, and a preset temperature coefficient.

[0022] Furthermore, the identification and deduction module issues a maintenance reminder when the number of license plate characters is less than the standard total number of characters;

[0023] The recognition and deduction module records the duration when the number of license plate characters is equal to the standard total number of characters, and enters the license plate characters and deducts the fees when the duration is greater than or equal to the standard duration.

[0024] Furthermore, when the number of license plate characters is equal to the standard total number of characters and the duration is less than the standard duration, the recognition and deduction module stores the video of the vehicle passing through the monitoring area and increases and adjusts the monitoring distance according to the duration, the standard duration and a preset distance coefficient.

[0025] Compared with the prior art, the beneficial effect of the present invention is that, through advanced data acquisition and processing technology, the accuracy of license plate recognition and the reliability of the system are greatly improved. The system collects license plate images through image sensors in the environmental monitoring area, and uses character recognition and judgment units for high-precision recognition, ensuring that high recognition rates can be maintained even under severe weather conditions. By real-time monitoring of vehicle speed and image clarity, the system can dynamically adjust the heating temperature to prevent image blur and equipment failure. The environmental judgment unit automatically adjusts system parameters for interfering weather such as rain and snow, thereby improving the stability of license plate recognition under various climatic conditions. In addition, the system's recognition and deduction module can not only accurately identify license plate characters, but also record videos of vehicles passing by, providing reliable data for subsequent analysis and troubleshooting, effectively solving the problem of low accuracy of license plate information recognition under extreme weather conditions due to reliance on light sources and light sensors.

[0026] Furthermore, through this judgment mechanism based on the character recognition ratio, the system can automatically start the environmental judgment unit when the character recognition does not meet the standard, effectively dealing with the decline in recognition accuracy caused by environmental factors or image quality problems. This automatic adjustment mechanism not only improves the accuracy of license plate recognition, but also reduces misrecognition caused by blurred images or missing characters.

[0027] Furthermore, through the dynamic environment judgment mechanism, the system can automatically respond to image acquisition problems caused by bad weather, ensuring that the image sensor can still work normally under interfering weather conditions, improving the reliability of license plate recognition, and reducing recognition failures caused by weather changes.

[0028] Furthermore, by normalizing the clarity score, the system can dynamically adjust image processing parameters to reduce recognition errors caused by image blur.

[0029] Furthermore, by calculating the vehicle speed score, the system can accurately evaluate the impact of vehicle speed on the clarity of the license plate image and timely adjust the image processing strategy to cope with the image quality at different speeds. This helps to maintain the clarity of the license plate image when the vehicle is driving at high speed and reduce the blur problem caused by excessive speed.

[0030] Furthermore, by combining the clarity weight and the vehicle speed weight, the system can comprehensively evaluate the quality of the license plate image to ensure high recognition accuracy under different vehicle speeds and image clarity conditions.

[0031] Furthermore, through this matching comparison and automatic adjustment of the heating temperature mechanism, the system can dynamically respond to environmental changes and the impact of equipment status, ensuring high-quality license plate image acquisition in all situations.

[0032] Furthermore, by combining the standard matching degree, the current matching degree and the temperature coefficient, the environmental correction unit can dynamically adjust the heating temperature to cope with the impact of different environmental conditions on the image quality.

[0033] Furthermore, through the segmented identification and judgment mechanism, the system can promptly detect and prompt potential identification problems or equipment failures to ensure the normal operation and maintenance of the system.

[0034] Furthermore, optimizing the subsequent recognition process by storing video data and adjusting the monitoring distance helps to improve the accuracy and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic diagram of an electronic toll collection system based on high-precision recognition according to this embodiment;

[0036] Figure 2 A determination logic diagram for determining a detection environment by a character recognition determination unit in this embodiment;

[0037] Figure 3 A determination logic diagram of the character recognition determination unit of this embodiment determining whether to heat the image sensor;

[0038] Figure 4 This is a decision logic diagram for the character recognition decision unit of this embodiment to determine the correction heating temperature. DETAILED DESCRIPTION

[0039] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0040] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0041] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0042] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0043] See also Figure 1 As shown, it is a schematic diagram of the electronic toll collection system based on high-precision recognition in this embodiment;

[0044] This embodiment provides an electronic toll collection system based on high-precision recognition, including:

[0045] A data acquisition module, comprising an image sensor for acquiring real-time license plate images of each vehicle in the monitoring area, a weather sensor for acquiring real-time weather information in the monitoring area, and a vehicle speed sensor for acquiring real-time vehicle speeds of each vehicle in the monitoring area, wherein the monitoring area comprises an environment monitoring area, a vehicle speed monitoring area, and a toll deduction area, and the length of the environment monitoring area is a preset monitoring distance;

[0046] The data acquisition module further includes a heating unit disposed near the image sensor;

[0047] An information processing module is connected to the data acquisition module, and includes a character recognition and determination unit and an environment determination unit. The character recognition and determination unit is used to use its built-in deep learning model to recognize the license plate characters of the real-time license plate image collected by the image sensor in the environmental monitoring area, and to make a determination based on the number of license plate characters and a preset standard character ratio; the environment determination unit is used to make a determination based on the determination result of the character recognition and determination unit according to the real-time weather information collected by the weather sensor and the preset interference weather information, and to operate the heating unit at a preset heating temperature according to the determination result;

[0048] Among them, the deep learning model can use convolutional neural networks, which can automatically learn the feature representation of images and is very suitable for license plate recognition. It can also use recurrent neural networks, especially long short-term memory networks, which can process sequence data and are very helpful for identifying continuous character sequences. There are also regional convolutional neural networks that can identify specific areas in the image and are suitable for license plate positioning.

[0049] The information processing module further includes a clarity recognition and determination unit and an environment correction unit. The clarity recognition and determination unit is used to use its built-in clarity recognition model to recognize the clarity of the real-time license plate image collected by the image sensor in the vehicle speed monitoring area, and make a judgment based on the clarity, the real-time vehicle speed collected by the vehicle speed sensor in the vehicle speed monitoring area, and a preset standard matching degree; the environment correction unit is used to correct the heating temperature based on the judgment result of the clarity recognition and determination unit and the standard matching degree, and operate the heating unit at the corrected heating temperature;

[0050] Among them, the clarity recognition model can use SRCNN, ESPCN and EDSR algorithms to utilize convolutional neural networks to perform super-resolution reconstruction of images, thereby improving the clarity of the image. It can also use generative adversarial networks to generate realistic high-resolution images through adversarial training.

[0051] The identification and deduction module is connected to the information processing module and the data acquisition module respectively, and is used to use its built-in deep learning model to identify the license plate characters of the real-time license plate image collected by the image sensor in the deduction area, make a judgment based on the number of license plate characters and a preset standard duration, and store the video of the vehicle passing through the monitoring area and adjust the monitoring distance based on the judgment result, or enter the license plate characters and deduct the fee, or issue a maintenance reminder.

[0052] Among them, the deep learning model can use the same model in the information processing module to ensure the consistency of previous and subsequent recognition.

[0053] The environmental monitoring area is an area used to monitor environmental conditions. Its main purpose is to collect information about the impact of weather and environment on license plate recognition. In this area, the system uses weather sensors to obtain real-time weather data in order to adjust system parameters (such as the operation of the heating unit) to improve the accuracy of license plate recognition in adverse weather conditions such as rain and snow.

[0054] The speed monitoring area is an area used to monitor vehicle speed. In this area, the speed sensor measures the real-time speed of passing vehicles. The system uses this data to determine the clarity of the license plate image and adjust the image quality at different speeds. Since excessive speed will affect the clarity of the license plate image, the speed monitoring area helps the system adjust the image processing parameters to ensure that the license plate information can be effectively recognized even when driving at high speeds.

[0055] The toll collection area is an area used to process tolls. In this area, the system will collect license plate images through image sensors and perform character recognition to determine the identity of the vehicle. Based on the recognition results, the system will perform the corresponding toll collection operation. When the vehicle passes through the toll collection area, the system will record the license plate information and calculate the fee to complete the toll collection process. If the license plate information cannot be recognized or the system detects a problem, it may trigger a maintenance prompt or perform other processing.

[0056] The setting of these three areas helps the system to process environmental data, vehicle speed data and charging operations respectively at different stages, ensuring the efficiency and accuracy of the overall charging process.

[0057] The standard character ratio refers to the ratio of the number of characters actually recognized in license plate recognition to the number of standard total characters, which is used to judge the accuracy of recognition. It is usually set to 0.9, which ensures that the system can recognize most license plate characters and reduce recognition errors. This embodiment is set to 0.9, depending on the accuracy of the character recognition technology and the tolerance to recognition errors, which can improve the recognition accuracy and reduce misjudgment.

[0058] The preset interfering weather information refers to the weather conditions that the system identifies as having a negative impact on license plate recognition, such as rain and snow. It is usually set to rain and snow, which can trigger the system's countermeasures to reduce recognition errors. This embodiment is set to rain and snow, depending on the significant impact of these weather conditions on image clarity and recognition accuracy, thereby ensuring that the system can automatically adjust and maintain recognition performance in bad weather.

[0059] The preset heating temperature refers to the operating temperature of the heating unit set by the system under interfering weather conditions. It is usually set to 40°C, which ensures the normal operation of the image sensor in low temperature or humid environments. This embodiment is set to 40°C, depending on the cold resistance of the equipment and environmental conditions, which can prevent frost or moisture on the image sensor due to bad weather and maintain the clarity of the license plate image.

[0060] The preset standard matching degree refers to the matching degree between the clarity of the license plate image and the vehicle speed, which is used to ensure the quality of the license plate image under high-speed driving conditions. It is usually set to 0.8, which ensures that the clarity of the license plate image is sufficient for accurate recognition when the vehicle speed is high. This embodiment is set to 0.8, depending on the impact of the vehicle speed on the image clarity, so that the license plate image can still be effectively recognized when driving at high speeds.

[0061] The preset standard duration refers to the time that the license plate image needs to exist in the toll deduction area to confirm the stability of the image. It is usually set to 0.5 seconds, which ensures that the system has enough time to process and confirm the license plate information. In this embodiment, it is set to 0.5 seconds, depending on the time requirement for image processing and the speed of the vehicle passing by, which can reduce recognition errors caused by instantaneous image blur and ensure accurate charging.

[0062] The data acquisition module obtains the license plate image, weather information and vehicle speed data in the monitoring area. In the environmental monitoring area, the image sensor collects the license plate image and determines the number of characters and the standard character ratio through the character recognition and judgment unit. If the recognition result is insufficient, the environmental judgment unit will determine whether the heating unit needs to be activated based on the real-time weather information and the preset interference weather information. The image clarity in the speed monitoring area is evaluated by the clarity recognition and judgment unit, and the heating temperature is corrected in combination with the speed information and the standard matching degree. In the deduction area, the system recognizes the license plate characters and makes judgments based on the standard duration, and finally executes deductions, video storage or issues maintenance prompts.

[0063] Through advanced data acquisition and processing technology, the accuracy of license plate recognition and the reliability of the system have been greatly improved. The system collects license plate images through image sensors in the environmental monitoring area, and uses character recognition and judgment units for high-precision recognition, ensuring that high recognition rates can be maintained even in adverse weather conditions. By monitoring vehicle speed and image clarity in real time, the system can dynamically adjust the heating temperature to prevent image blur and equipment failure. The environmental judgment unit automatically adjusts system parameters for interfering weather such as rain and snow, thereby improving the stability of license plate recognition under various climatic conditions. In addition, the system's recognition and deduction module can not only accurately identify license plate characters, but also record videos of vehicles passing by, providing reliable data for subsequent analysis and troubleshooting.

[0064] Please continue reading Figure 2 As shown, it is a decision logic diagram of the character recognition decision unit of this embodiment for determining the detection environment;

[0065] Specifically, the character recognition determination unit determines according to the number of license plate characters and a preset standard character ratio:

[0066] The character recognition determination unit is provided with a standard total number of characters, and the ratio of the number of license plate characters to the standard total number of characters is calculated to obtain a character recognition ratio. When the character recognition ratio is less than the standard character ratio, the environment determination unit is enabled.

[0067] After receiving the license plate image captured by the image sensor, the character recognition and determination unit first extracts the characters in the license plate and counts their number. Then, the ratio between the number of characters actually recognized and the set standard total number of characters is calculated to obtain the character recognition ratio. If the calculated character recognition ratio is lower than the preset standard character ratio, the system will automatically trigger the environment determination unit to further determine whether it is necessary to adjust the processing strategy or enable other remedial measures.

[0068] Through this judgment mechanism based on the character recognition ratio, the system can automatically start the environmental judgment unit when the character recognition does not meet the standard, effectively dealing with the decline in recognition accuracy caused by environmental factors or image quality problems. This automatic adjustment mechanism not only improves the accuracy of license plate recognition, but also reduces misrecognition caused by blurred images or missing characters.

[0069] Please continue reading Figure 3 As shown, it is a determination logic diagram of the character recognition determination unit of this embodiment determining whether to heat the image sensor;

[0070] Specifically, the environment determination unit makes a determination according to the determination result of the character recognition determination unit according to the real-time weather information collected by the weather sensor and the preset interference weather information, including:

[0071] When the character recognition determination unit determines to enable the environment determination unit, the environment determination unit determines that the image sensor needs to be heated when the real-time weather information collected by the weather sensor is interference weather information.

[0072] When the character recognition judgment unit finds that the license plate character recognition ratio is lower than the preset standard, the environment judgment unit will be enabled. The environment judgment unit compares the real-time weather information provided by the weather sensor with the preset interference weather information. If the real-time weather information matches the interference weather information (such as rain or snow), the environment judgment unit will determine that the image sensor needs to be heated to reduce the impact of weather on image acquisition, thereby ensuring the accuracy of license plate recognition.

[0073] Through the dynamic environment judgment mechanism, the system can automatically respond to image acquisition problems caused by bad weather, ensuring that the image sensor can still work normally under interfering weather conditions, improving the reliability of license plate recognition, and reducing recognition failures caused by weather changes.

[0074] Specifically, the clarity recognition and determination unit recognizes the clarity of the real-time license plate image collected by the image sensor in the vehicle speed monitoring area, including:

[0075] The clarity recognition and determination unit uses an image processing algorithm to recognize the clarity of the real-time license plate image, and standardizes the clarity of the real-time license plate image according to a preset standard clarity to obtain a clarity score.

[0076] The clarity recognition and determination unit uses an image processing algorithm to analyze the license plate image collected in real time in the speed monitoring area and calculate the clarity of the image. The algorithm compares the actual clarity of the image with the preset standard clarity and obtains a clarity score through standardization to evaluate the quality of the license plate image.

[0077] By standardizing the clarity score, the system can dynamically adjust image processing parameters to reduce recognition errors caused by image blur.

[0078] Specifically, the clarity recognition and judgment unit is provided with a standard vehicle speed, calculates the absolute value of the difference between the real-time vehicle speed collected in the speed monitoring area and the standard vehicle speed, calculates the ratio of the absolute value to the standard vehicle speed, calculates the difference between 1 and the ratio, and obtains the vehicle speed score.

[0079] The clarity recognition judgment unit sets a standard speed as a reference. It first calculates the absolute value of the difference between the actual speed and the standard speed, then calculates the ratio of this absolute value to the standard speed, and then subtracts this ratio from 1 to get a speed score. This process helps evaluate the impact of speed on the clarity of the license plate image.

[0080] By calculating the speed score, the system can accurately evaluate the impact of vehicle speed on the clarity of the license plate image and timely adjust the image processing strategy to cope with the image quality at different speeds. This helps maintain the clarity of the license plate image when the vehicle is driving at high speed and reduce the blur problem caused by excessive speed.

[0081] Specifically, the clarity recognition and judgment unit is provided with a clarity weight and a vehicle speed weight, and the product of the clarity weight and the clarity score, the product of the vehicle speed weight and the vehicle speed score, and the sum of the product of the clarity weight and the clarity score and the product of the vehicle speed weight and the vehicle speed score are calculated to obtain the matching degree.

[0082] The clarity weight refers to the importance coefficient assigned to the clarity score when evaluating the image matching degree. The clarity weight depends on the system's evaluation of the impact of image quality on the recognition process. It is usually set to 0.6-0.8, and is set to 0.7 in this embodiment. Such a setting can ensure that the image clarity occupies a higher weight in the matching degree calculation, thereby improving the accuracy of recognition.

[0083] The speed weight refers to the importance factor assigned to the speed score when evaluating the image matching degree. The speed weight depends on the degree of influence of the speed on the image stability and clarity. It is usually set to 0.2-0.4, and is set to 0.3 in this embodiment. Such a setting can ensure that the influence of the speed on the image quality is properly considered, thereby maintaining the stability of recognition under high-speed driving conditions.

[0084] The clarity recognition judgment unit is equipped with clarity weight and vehicle speed weight. The system first calculates the product of the clarity weight and the clarity score, then calculates the product of the vehicle speed weight and the vehicle speed score, and then adds these two products to obtain the final matching degree. The matching degree is used to evaluate the overall quality of the image and the reliability of recognition.

[0085] By combining the clarity weight and the vehicle speed weight, the system can comprehensively evaluate the quality of the license plate image to ensure high recognition accuracy under different vehicle speeds and image clarity conditions.

[0086] Please continue reading Figure 4 As shown, it is a decision logic diagram of the character recognition decision unit of this embodiment for determining the correction heating temperature;

[0087] Specifically, the clarity recognition and determination unit determines that the heating temperature needs to be corrected when the matching degree is less than the standard matching degree.

[0088] After calculating the image matching degree, the clarity recognition judgment unit compares it with the preset standard matching degree. If the matching degree is less than the standard matching degree, the system will determine that the current environment or equipment status is not good, and then trigger the correction mechanism to adjust the temperature of the heating unit to improve the working environment of the image sensor and ensure the clarity and recognition rate of the license plate image.

[0089] Through matching comparison and automatic adjustment of heating temperature, the system can dynamically respond to environmental changes and equipment status, ensuring high-quality license plate image acquisition in all situations.

[0090] Specifically, when the clarity recognition and determination unit determines that the heating temperature needs to be corrected, the environment correction unit increases the corrected heating temperature according to the standard matching degree correction heating temperature, the matching degree, and a preset temperature coefficient.

[0091] The preset temperature coefficient is a parameter used to adjust the heating temperature, which determines the amount of increase in the heating temperature when the matching degree is insufficient. The temperature coefficient depends on the heating capacity of the device and the required temperature adjustment range. It is usually set to 1.1-1.5, and is set to 1.2 in this embodiment. Such a setting can quickly and effectively increase the heating temperature when the matching degree is below the standard, thereby improving the working environment of the image sensor and ensuring the clarity of the license plate image.

[0092] When the clarity recognition and determination unit determines that the heating temperature needs to be corrected, the environment correction unit will calculate the new heating temperature based on the standard matching degree, the current matching degree and the preset temperature coefficient. The environment correction unit increases the temperature of the heating unit based on the comprehensive calculation results of these three parameters, thereby improving the working environment of the image sensor and ensuring the clarity of the license plate image.

[0093] By combining the standard match, current match and temperature coefficient, the environmental correction unit can dynamically adjust the heating temperature to cope with the impact of different environmental conditions on image quality.

[0094] Specifically, the recognition and deduction module issues a maintenance reminder when the number of license plate characters is less than the standard total number of characters;

[0095] The recognition and deduction module records the duration when the number of license plate characters is equal to the standard total number of characters, and enters the license plate characters and deducts the fees when the duration is greater than or equal to the standard duration.

[0096] The recognition and deduction module first determines the number of license plate characters. If the number of license plate characters is less than the standard total number of characters, the system will issue a maintenance prompt, indicating that there may be a recognition problem or equipment failure. If the number of license plate characters is equal to the standard total number of characters, the system will record the duration of the license plate characters. When the duration is greater than or equal to the preset standard duration, the system will enter the license plate characters and perform the deduction operation.

[0097] Through the segmented identification and judgment mechanism, the system can promptly detect and prompt potential identification problems or equipment failures to ensure the normal operation and maintenance of the system.

[0098] Specifically, when the number of license plate characters is equal to the standard total number of characters and the duration is less than the standard duration, the recognition and deduction module stores the video of the vehicle passing through the monitoring area and adjusts the monitoring distance according to the duration, the standard duration and the preset distance coefficient.

[0099] When the recognition and deduction module detects that the number of license plate characters is equal to the standard total number of characters, but the duration is less than the standard duration, it will store the video of the vehicle passing through the monitoring area. Then, the system calculates and increases the monitoring distance based on the duration, standard duration and preset distance coefficient to improve the recognition accuracy in the next detection.

[0100] Storing video data and adjusting the monitoring distance to optimize the subsequent recognition process helps improve the accuracy and reliability of the system.

[0101] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0102] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An electronic toll collection system based on high-precision recognition, characterized in that: include: A data acquisition module, comprising an image sensor for acquiring real-time license plate images of each vehicle in the monitoring area, a weather sensor for acquiring real-time weather information in the monitoring area, and a vehicle speed sensor for acquiring real-time vehicle speeds of each vehicle in the monitoring area, wherein the monitoring area comprises an environment monitoring area, a vehicle speed monitoring area, and a toll deduction area, and the length of the environment monitoring area is a preset monitoring distance; The data acquisition module further includes a heating unit disposed near the image sensor; An information processing module, connected to the data acquisition module, comprising a character recognition and determination unit and an environment determination unit, wherein the character recognition and determination unit is used to recognize the license plate characters of the real-time license plate image acquired by the image sensor in the environment monitoring area, and to make a determination based on the number of license plate characters and a preset standard character ratio; The environment determination unit is used to make a determination according to the determination result of the character recognition determination unit based on the real-time weather information collected by the weather sensor and the preset interference weather information, and operate the heating unit at a preset heating temperature according to the determination result; The information processing module also includes a clarity recognition and determination unit and an environment correction unit, wherein the clarity recognition and determination unit is used to identify the clarity of the real-time license plate image collected by the image sensor in the vehicle speed monitoring area, and to make a determination based on the clarity, the real-time vehicle speed collected by the vehicle speed sensor in the vehicle speed monitoring area, and a preset standard matching degree; The environment correction unit is used to correct the heating temperature according to the determination result of the clarity recognition determination unit and the standard matching degree, and operate the heating unit at the corrected heating temperature; The identification and deduction module is connected to the information processing module and the data acquisition module respectively, and is used to identify the license plate characters of the real-time license plate image collected by the image sensor in the deduction area, make a judgment based on the number of license plate characters and a preset standard duration, and store the video of the vehicle passing through the monitoring area and adjust the monitoring distance based on the judgment result, or enter the license plate characters and make a deduction, or issue a maintenance reminder.

2. The electronic toll collection system based on high-precision recognition according to claim 1 is characterized in that: The character recognition determination unit determines according to the number of license plate characters and the preset standard character ratio: The character recognition determination unit is provided with a standard total number of characters, and the ratio of the number of license plate characters to the standard total number of characters is calculated to obtain a character recognition ratio. When the character recognition ratio is less than the standard character ratio, the environment determination unit is enabled.

3. The electronic toll collection system based on high-precision recognition according to claim 2 is characterized in that: The environment determination unit makes a determination according to the determination result of the character recognition determination unit according to the real-time weather information collected by the weather sensor and the preset interference weather information, including: When the character recognition determination unit determines to enable the environment determination unit, the environment determination unit determines that the image sensor needs to be heated when the real-time weather information collected by the weather sensor is interference weather information.

4. The electronic toll collection system based on high-precision recognition according to claim 3 is characterized in that: The definition recognition and determination unit recognizes the definition of the real-time license plate image collected by the image sensor in the vehicle speed monitoring area, including: The clarity recognition and determination unit uses an image processing algorithm to recognize the clarity of the real-time license plate image, and standardizes the clarity of the real-time license plate image according to a preset standard clarity to obtain a clarity score.

5. The electronic toll collection system based on high-precision recognition according to claim 4 is characterized in that: The clarity recognition and judgment unit is provided with a standard vehicle speed, and the absolute value of the difference between the real-time vehicle speed collected in the vehicle speed monitoring area and the standard vehicle speed is calculated, the ratio of the absolute value to the standard vehicle speed is calculated, and the difference between 1 and the ratio is calculated to obtain a vehicle speed score.

6. The electronic toll collection system based on high-precision recognition according to claim 5 is characterized in that: The clarity recognition and judgment unit is provided with a clarity weight and a vehicle speed weight, calculates the product of the clarity weight and the clarity score, calculates the product of the vehicle speed weight and the vehicle speed score, and calculates the sum of the product of the clarity weight and the clarity score and the product of the vehicle speed weight and the vehicle speed score to obtain a matching degree.

7. The electronic toll collection system based on high-precision recognition according to claim 6 is characterized in that: The clarity recognition and determination unit determines that the heating temperature needs to be corrected when the matching degree is less than the standard matching degree.

8. The electronic toll collection system based on high-precision recognition according to claim 7 is characterized in that: When the clarity recognition and determination unit determines that the heating temperature needs to be corrected, the environment correction unit increases the corrected heating temperature according to the standard matching degree correction heating temperature, the matching degree, and a preset temperature coefficient.

9. The electronic toll collection system based on high-precision recognition according to claim 8 is characterized in that: The recognition and deduction module issues a maintenance reminder when the number of license plate characters is less than the standard total number of characters; The recognition and deduction module records the duration when the number of license plate characters is equal to the standard total number of characters, and enters the license plate characters and deducts the fees when the duration is greater than or equal to the standard duration.

10. The electronic toll collection system based on high-precision recognition according to claim 9 is characterized in that: When the number of license plate characters is equal to the standard total number of characters and the duration is less than the standard duration, the recognition and deduction module stores the video of the vehicle passing through the monitoring area and increases and adjusts the monitoring distance according to the duration, the standard duration and the preset distance coefficient.

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