Automatic charging billing method based on identity recognition, charging pile, product and medium

Abstract

The invention discloses an automatic charging billing method based on identity recognition, a charging pile, a product and a medium, and relates to the field of electric vehicle charging. The method comprises the steps of recognizing a first license plate image of a target vehicle through a license plate recognition model to obtain first vehicle identity information of the target vehicle; when the confidence coefficient of the first vehicle identity information is smaller than a preset value, whether the license plate of the target vehicle is shielded by stains is judged; if yes, generating a cleaning control instruction according to the license plate position information of the target vehicle; sending the cleaning control instruction to cleaning equipment to clean the license plate; after the cleaning equipment completes license plate cleaning, a second license plate image of the target vehicle is recognized through the license plate recognition model, and second vehicle identity information of the target vehicle is obtained; and binding the charging billing of the target vehicle with the identity information of the second vehicle. According to the invention, through intelligent identification and cleaning of the license plate, accurate identification of the vehicle identity and accurate charging billing are ensured, so that the operation efficiency of the charging station and the charging experience of a user are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric vehicle charging, and in particular to an automatic charging billing method based on identity recognition, a charging pile, a product and a medium. Background Art

[0002] With the global focus on sustainable energy and reducing carbon emissions, the electric vehicle industry is developing rapidly. The growth of electric vehicles has driven the demand for charging infrastructure. The use of charging stations is becoming more and more popular.

[0003] When charging a charging pile, users are required to manually enter the license plate number to bind it, which is a cumbersome operation. In order to improve user-friendliness, the charging pile in the relevant technology uses license plate recognition technology, which captures the license plate image of the vehicle through a high-definition camera installed at the charging station, and then uses image processing and pattern recognition algorithms to automatically extract the license plate number, associate the vehicle with the charging pile, and realize automated identity authentication and billing process, thereby improving charging efficiency, reducing manual operations, and improving user experience.

[0004] However, the accuracy of license plate recognition may be affected by factors such as stains, light changes, license plate damage or occlusion, resulting in license plate recognition errors and thus inability to accurately bill the charged vehicle. Summary of the invention

[0005] In view of the above-mentioned technical problems and defects, the purpose of the present invention is to provide an automatic charging and billing method, charging pile, product and medium based on identity recognition, which ensures accurate identification of vehicle identity and accurate charging billing through intelligent recognition and cleaning of license plates, thereby significantly improving the operating efficiency of charging stations and user charging experience.

[0006] To achieve the above-mentioned objectives, in a first aspect, the present invention provides an automatic charging and billing method based on identity recognition, which is applied to a charging pile, and the method includes: after a target vehicle enters a charging parking space, identifying a first license plate image of the target vehicle through a license plate recognition model to obtain the first vehicle identity information of the target vehicle; when the confidence level of the first vehicle identity information is less than a preset value, determining whether the license plate of the target vehicle is blocked by stains; if so, generating a cleaning control instruction according to the license plate position information of the target vehicle; sending the cleaning control instruction to a cleaning device, so that the cleaning device performs a cleaning operation on the license plate of the target vehicle according to the cleaning control instruction; when the cleaning device completes cleaning the license plate, identifying a second license plate image of the target vehicle through the license plate recognition model to obtain the second vehicle identity information of the target vehicle; and binding the charging billing of the target vehicle to the second vehicle identity information.

[0007] By adopting the technical solution of the present invention, the identity information of the vehicle entering the charging parking space is automatically obtained through the license plate recognition model, realizing a vehicle identification process without human intervention. When the charging pile detects that the confidence of the license plate recognition is lower than the preset threshold, that is, it is considered that the recognition result may be inaccurate, it is further determined whether the license plate is blocked by stains and affects the recognition accuracy. If it is judged to be blocked by stains, the charging pile will automatically generate a cleaning control instruction and send it to the cleaning equipment to perform precise cleaning operations. This automated cleaning process not only improves the cleaning efficiency, but also ensures the cleaning quality, thereby providing a clear image basis for the re-identification of the license plate. After the cleaning is completed, the charging pile performs license plate recognition again, obtains the updated vehicle identity information, and binds it to the charging billing, ensuring the accuracy of the billing and the consistency of the vehicle identity.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the step of determining whether the license plate of the target vehicle is obscured by stains includes: obtaining texture structure information of the license plate image, the texture structure information including uniformity, roughness and directionality; and determining whether the license plate of the target vehicle is obscured by stains based on the texture structure information.

[0009] The above scheme provides a more comprehensive image quality assessment for the recognition system by obtaining the texture structure information of the license plate image, including uniformity, roughness and directionality. This method can more accurately determine whether the license plate is obscured by stains, because changes in texture are often a direct manifestation of the presence of stains. This comprehensive assessment improves the robustness of the recognition system and maintains a high recognition accuracy rate even under the influence of stains, thereby reducing user inconvenience and charging service interruptions caused by recognition errors.

[0010] In combination with some embodiments of the first aspect, in some embodiments, the step of determining whether the license plate of the target vehicle is obscured by stains includes: obtaining stain features in the license plate image; determining a proportion of the stain area in the license plate image based on the stain features; and determining whether the license plate of the target vehicle is obscured by stains based on the proportion of the stain area.

[0011] The above scheme provides a direct and effective method for judging stain occlusion by identifying the features of stains in the license plate image and quantifying the proportion of the stain area. This method can accurately assess the degree of influence of stains on license plate recognition and avoid the misjudgment that may be caused by simple threshold judgment. By calculating the specific proportion, it is possible to more flexibly decide whether a cleaning operation is needed, optimize the use of cleaning resources, reduce unnecessary cleaning, and improve the operating efficiency of the charging station.

[0012] In combination with some embodiments of the first aspect, in some embodiments, the step of determining whether the license plate of the target vehicle is obscured by stains includes: obtaining image quality information of the license plate image, the image quality information including clarity, contrast, and brightness; determining an image quality evaluation result of the license plate image based on the image quality information; and determining whether the license plate of the target vehicle is obscured by stains based on the image quality evaluation result.

[0013] The above scheme provides a stain occlusion judgment method based on image quality by obtaining image quality information such as the clarity, contrast and brightness of the license plate image. This method focuses on the visual quality of the image and can quickly identify visual obstructions caused by stains. By combining these indicators, a more reasonable judgment can be made to ensure that the cleaning procedure is only started when the image quality is indeed affected by stains, thereby avoiding excessive cleaning and improving the intelligence level of the charging pile.

[0014] In combination with some embodiments of the first aspect, in some embodiments, the step of determining the image quality assessment result of the license plate image based on the image quality information includes: respectively obtaining a clarity score, a contrast score, and a brightness score of the license plate image; determining the image quality score of the license plate image based on the clarity score, the contrast score, and the brightness score; and determining the image quality score as the image quality assessment result.

[0015] The above scheme provides a quantitative image quality assessment method for charging piles by obtaining the scores of clarity, contrast and brightness respectively and determining the comprehensive image quality score of the license plate image accordingly. This method makes the image quality assessment more detailed and precise, which helps the system to more accurately determine whether the license plate image is suitable for recognition. The use of comprehensive scores improves the decision-making quality of charging piles and ensures consistent recognition performance under different conditions.

[0016] In combination with some embodiments of the first aspect, in some embodiments, before the step of binding the charging billing of the target vehicle with the second vehicle identity information, it also includes: obtaining a facial image of the target user in the charging parking space; recognizing the facial image through a facial recognition model to obtain the user identity information of the target user; determining whether the user identity information matches the second vehicle identity information; if so, starting charging billing for the target vehicle.

[0017] The above solution implements double verification of user identity by adding a facial recognition step before charging billing. This method not only improves charging safety and prevents unauthorized use, but also enhances user experience by ensuring that the user identity matches the vehicle identity, avoiding charging service rejection due to identity mismatch. This double verification mechanism significantly improves the reliability of charging services and user trust.

[0018] In combination with some embodiments of the first aspect, in some embodiments, the step of generating a cleaning control instruction based on the license plate position information of the target vehicle includes: determining the direction angle and distance of the nozzle of the cleaning equipment relative to the license plate based on the license plate position information of the target vehicle; determining the water spray angle and water pressure of the nozzle based on the direction angle and distance; and generating a cleaning control instruction based on the water spray angle and water pressure.

[0019] The above solution provides precise operating parameters for the cleaning equipment by intelligently generating cleaning control instructions based on the license plate location information, including water spray angle and water pressure. This method ensures the accuracy and effectiveness of the cleaning operation and avoids poor cleaning results or damage to the vehicle due to improper operation. Through intelligent control instruction generation, cleaning efficiency is improved, manual intervention is reduced, and the automation level and service quality of the charging station are further improved.

[0020] In a second aspect, the present invention provides a charging pile, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the charging pile to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, the present invention provides a computer program product comprising instructions, and when the computer program product is run on a charging pile, the charging pile executes the method described in the first aspect and any possible implementation manner of the first aspect.

[0022] In a fourth aspect, the present invention provides a computer-readable storage medium storing instructions, which, when executed on a charging pile, enables the main control unit to execute the method described in the first aspect and any possible implementation of the first aspect.

[0023] It can be understood that the charging pile provided in the second aspect, the computer program product provided in the third aspect and the storage medium provided in the fourth aspect are all used to execute the method provided in the present invention. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here.

[0024] One or more technical solutions provided by the present invention have at least the following technical effects or advantages: 1. The present invention significantly improves the accuracy and robustness of license plate recognition by comprehensively evaluating the texture structure information and image quality indicators (such as clarity, contrast and brightness) of the license plate image. Even under stain occlusion or other unfavorable conditions, the system can accurately judge the status of the license plate and take corresponding measures, such as automatic cleaning, to ensure the quality of the license plate image, thereby ensuring the accurate identification of the vehicle identity and the smooth charging and billing.

[0025] 2. The integrated automated cleaning equipment and intelligent identification system of the present invention greatly optimize the user's charging experience. Users do not need to manually clean the license plate or perform tedious identity verification. The charging pile can automatically identify the vehicle and start the charging process. In addition, through the intelligent generation of cleaning control instructions, the system ensures the efficiency and accuracy of the cleaning operation, avoids user waiting and charging interruption, and significantly improves the charging efficiency.

[0026] 3. The present invention introduces face recognition technology to authenticate users and matches it with vehicle identity information. This technical solution enhances the safety of the charging process and ensures that only authorized users can charge their vehicles. At the same time, charging billing is bound to vehicle identity information to ensure the transparency and accuracy of the billing process, avoid billing errors and disputes, and improve the reliability of charging services and user trust. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings herein are incorporated into and constitute a part of the specification, showing embodiments consistent with the present invention, and together with the specification, are used to explain the principles of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings: Figure 1 is a flow chart of an automatic charging and billing method based on identity recognition according to an embodiment of the present invention; Figure 2 is a flow chart of another automatic charging billing method based on identity recognition according to an embodiment of the present invention; Figure 3 It is a schematic diagram of the architecture of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The terms used in the following embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to be limiting of the present invention. As used in the specification of the present invention, the singular expressions "a", "a", "above", "the" and "this" are intended to also include plural expressions, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present invention refers to any or all possible combinations comprising one or more of the listed items.

[0029] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood as implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present invention, unless otherwise specified, the meaning of "plurality" is two or more.

[0030] It should also be noted that, unless otherwise clearly specified and limited, in the embodiments of the present invention, the terms such as "setting" and "connection" should be understood in a broad sense. For example, "connection" 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 an indirect connection through an intermediate medium, it can be the internal connection of two components; it can be a wired communication connection or a wireless communication connection. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. The embodiments of the present invention are described in detail below.

[0031] In traditional technology, when an electric car enters a charging station and stops at a designated parking space, the high-definition camera on the charging pile automatically captures the vehicle's license plate image. The charging pile analyzes the image through the built-in license plate recognition software, extracts the license plate number and matches it with the vehicle information registered in the database. Once the system confirms the identity of the vehicle, the corresponding charging pile will automatically start the charging process or through the owner's selection on the touch screen. A more convenient and automated charging experience is achieved.

[0032] However, when a vehicle is driven in bad weather or poor road conditions, the license plate may be obscured by ice, snow, mud or other stains, which can seriously affect the accuracy of the license plate recognition system. Since license plate recognition technology relies on clear visual images to capture and analyze the characters and numbers on the license plate, any form of obstruction may cause the system to fail to correctly read the license plate information. For example, in winter, heavy snow may cover the license plate, making it difficult for the camera to capture a complete image of the license plate; on rainy days or muddy roads, mud spots may splash onto the license plate, blurring or partially covering the characters, causing the recognition algorithm to be unable to accurately parse the license plate number.

[0033] The stains may cause the license plate recognition system to misread and mistakenly identify the stains as part of the license plate, which may cause billing errors or fail to provide charging services for legal vehicles. This not only brings inconvenience to car owners, but may also affect the operating efficiency and service quality of charging stations.

[0034] In response to the above problems and defects, an embodiment of the present invention provides an automatic charging and billing method based on identity recognition. First, the identity information of the vehicle entering the charging parking space is automatically obtained through the license plate recognition model, realizing a vehicle identification process without manual intervention. When the charging pile detects that the confidence of the license plate recognition is lower than the preset threshold, that is, it is considered that the recognition result may be inaccurate, it is further determined whether the license plate is affected by the recognition accuracy due to the obstruction of stains. If it is judged to be obstructed by stains, the charging pile will automatically generate a cleaning control instruction and send it to the cleaning equipment to perform precise cleaning operations. This automated cleaning process not only improves the cleaning efficiency, but also ensures the cleaning quality, thereby providing a clear image basis for the re-identification of the license plate. After the cleaning is completed, the charging pile performs license plate recognition again, obtains the updated vehicle identity information, and binds it to the charging billing, ensuring the accuracy of the billing and the consistency of the vehicle identity.

[0035] Through this technical solution, the operation of charging piles has become more efficient and user-friendly. It not only reduces billing disputes caused by identification errors, but also improves the service quality and operational efficiency of charging stations. In addition, the automated cleaning and identification process reduces the reliance on manual operations.

[0036] Combine the following Figure 1 , to introduce the automatic charging billing method based on identity recognition of this embodiment, which specifically includes the following steps: Step 101: After a target vehicle enters a charging parking space, a first license plate image of the target vehicle is recognized by a license plate recognition model to obtain first vehicle identity information of the target vehicle.

[0037] After the target vehicle enters the charging parking space, the charging pile immediately starts its built-in license plate recognition model. First, the vehicle's license plate image is captured by a high-definition camera and the image content is analyzed in real time. The camera is aimed at the parking space to ensure a clear view of the license plate after the vehicle stops. The charging pile matches the image captured by the camera with the license plate information stored in the database to identify the vehicle. During the recognition process, the license plate recognition model evaluates the confidence of the recognition result to ensure the accuracy of the first vehicle identity information obtained. This step is the starting point for the automation of the charging billing process. The charging pile uses intelligent recognition technology to reduce the need for manual input, improve operational efficiency, and provide car owners with a convenient charging access method.

[0038] Among them, the license plate recognition model uses deep learning technology to achieve high-precision recognition of vehicle license plates. The model uses a large amount of labeled license plate image data for training, and automatically learns the features and patterns in the image through deep learning architectures such as convolutional neural networks (CNN). During the training process, the neural network continuously adjusts its internal parameters to improve its ability to recognize text and numbers on license plates.

[0039] In this embodiment, the vehicle identity information is a set of unique data used to uniquely identify and distinguish different vehicles. This usually includes the vehicle's license plate number, vehicle identification number (VIN), engine number, vehicle model, vehicle color, vehicle registration information, and other possible vehicle-specific details. In modern intelligent transportation systems, vehicle identity information is not only used for traffic management and security monitoring, but is also widely used in a variety of scenarios such as electronic toll collection, parking lot management, vehicle tracking, and emergency services.

[0040] Step 102: When the confidence level of the first vehicle identity information is less than a preset value, determine whether the license plate of the target vehicle is blocked by stains.

[0041] After the charging pile obtains the first vehicle identity information of the target vehicle, the next step is to evaluate the confidence of this information. The license plate recognition model analyzes the accuracy of the license plate recognition result and compares this result with the preset confidence threshold. If the confidence is insufficient, it is considered that there may be errors or uncertainties in the recognition result.

[0042] Image analysis technology is then used to check whether there are factors in the license plate image that may affect recognition accuracy, such as stains, obstructions or other visual interference. The charging pile can then intelligently identify whether the license plate has become difficult to recognize due to environmental factors, thus providing a decision-making basis for the next cleaning operation.

[0043] If it is determined that the license plate of the target vehicle is blocked by stains, the process proceeds to step 103; otherwise, the process returns to step 101, indicating that the license plate is not blocked by stains, and it is necessary to reacquire the license plate image of the target vehicle and perform recognition to obtain a vehicle identity information recognition result with a higher confidence level.

[0044] In some embodiments, this step may specifically include: first obtaining texture structure information of the license plate image, the texture structure information including uniformity, roughness and directionality, and then determining whether the license plate of the target vehicle is blocked by stains based on the texture structure information.

[0045] Among them, uniformity reflects the consistency of pixel grayscale values ​​in the image, roughness indicates the roughness of the texture in the image, and directionality reveals the arrangement direction of the image texture.

[0046] When the texture structure in an image changes due to the presence of stains, spots or other occlusions, texture analysis can detect this damage and identify the degradation of image quality or distortion of features. For example, in a license plate image, stains may cover or blur the letters and numbers on the license plate, causing the texture analysis results to be significantly different from the clean, clear license plate image. This difference can be used to assess whether the image is affected by stains, and then decide whether measures such as cleaning or image enhancement are needed to restore the original texture structure of the image and ensure the accuracy of license plate recognition.

[0047] Texture information may further include roughness or energy and contrast.

[0048] In this embodiment, the charging pile can extract texture structure information by using the gray level co-occurrence matrix (GLCM). The following are the specific steps and calculation methods: 1. Construct the gray level co-occurrence matrix (GLCM): First, a gray-level co-occurrence matrix is ​​created from the original image. For each pixel in the image, its gray value and the gray value of the adjacent pixels in a specific direction are recorded.

[0049] 2. Select the analysis direction: Select the direction of analysis, common ones are 0° (horizontal), 45°, 90° (vertical) and 135°. For each direction, construct a GLCM separately.

[0050] 3. Calculate homogeneity: Uniformity reflects the similarity of the grayscale values ​​of adjacent pixels in the image. The calculation formula is as follows: Where N is the number of gray levels and i and j are the gray level pairs in the GLCM.

[0051] 4. Calculate roughness (Angular Second Moment, ASM) or energy (Energy): Roughness or energy reflects the activity or drastic change of the image texture. The calculation formula is as follows: Among them, p(i,j) is the probability density function value of the corresponding gray level pair (i,j) in GLCM.

[0052] 5. Calculate the contrast: Contrast refers to the difference in grayscale between adjacent pixels. The calculation formula is as follows:

[0053] 6. Calculate Directionality: Directionality indicates the degree to which the texture is aligned along a particular direction. It can be assessed by comparing the contrast in different directions. The calculation formula can be:

[0054] 7. Calculate the correlation: Correlation represents the strength of the linear relationship between the grayscale values ​​of adjacent pixels. The calculation formula is as follows: Among them, μi and μj are the means of gray levels i and j, and σi and σj are their standard deviations.

[0055] In some embodiments, step 102 may further include the following steps: S11, obtaining stain features in the license plate image.

[0056] The charging pile will perform pre-processing operations such as graying and filtering on the captured license plate image to enhance the recognizability of stains in the image. Next, the charging pile uses image segmentation technology to distinguish the foreground (characters and borders) and background on the license plate. On this basis, specific algorithms are further applied, such as feature detection based on color, texture or shape, to identify and extract possible stain areas in the image. The key to this step is to accurately distinguish stains from other image features to ensure the accuracy of subsequent analysis.

[0057] For example, if there are spots of mud in the license plate image, the system may detect circular areas with high contrast with the license plate color and mark these areas as potential stain features.

[0058] S12, determining the proportion of the stain area in the license plate image according to the stain feature.

[0059] The charging station will calculate the total area of ​​the pixel area identified as stains and compare it with the area of ​​the entire license plate image to obtain the proportion of the stain area. This ratio is an important indicator for evaluating the degree of influence of stains on license plate recognition. If the proportion of the stain area exceeds the set threshold, it may mean that the stain is sufficient to affect the readability of the license plate.

[0060] S13, judging whether the license plate of the target vehicle is blocked by stains according to the proportion of the stain area.

[0061] The charging station will determine whether the license plate is obscured by stains to the extent that it affects recognition based on the proportion of the stain area.

[0062] Assuming that the charging pile determines through analysis that the proportion of the stained area has reached 30%, exceeding the threshold of 20%, the charging pile will automatically mark the license plate as "obstructed by stains".

[0063] In some embodiments, step 102 may further include the following steps: S21, obtaining image quality information of the license plate image, where the image quality information includes clarity, contrast and brightness.

[0064] Obtaining image quality information of license plate images is a technical analysis process, in which the charger will evaluate the three key indicators of image clarity, contrast and brightness. Clarity reflects the degree of discernibility of details in the image, usually determined by measuring the amplitude of high-frequency components in the image; contrast measures the difference between light and dark areas in the image, calculated by comparing the grayscale values ​​of the brightest and darkest pixels; brightness is the average light level of the image, obtained by averaging the grayscale values ​​of all pixels. This process usually involves complex image processing algorithms, including edge detection, histogram equalization and other technologies to ensure accurate assessment of image quality.

[0065] For example, if the edges of the license plate image are not detected to be sharp enough, this may indicate insufficient definition; if the grayscale difference between the characters on the license plate and the background is small, the contrast may be low; if the entire image looks too dark or too light, the brightness may be inappropriate.

[0066] S22, determining an image quality evaluation result of the license plate image according to the image quality information.

[0067] After obtaining the specific values ​​of clarity, contrast and brightness, these values ​​will be comprehensively evaluated according to preset standards or algorithms to determine the overall quality of the image. This may include setting thresholds to determine whether each indicator meets acceptable standards, or using methods such as weighted average to calculate a comprehensive image quality score. This score can provide quantitative results to determine whether the image is suitable for further processing, such as license plate recognition.

[0068] In some embodiments, this step may specifically include: S221, respectively obtaining a clarity score, a contrast score, and a brightness score of the license plate image.

[0069] The image processing system of the charging pile first performs a detailed analysis of the license plate image to evaluate its clarity, contrast, and brightness separately. The clarity score is determined by identifying high-frequency information and edge sharpness in the image, and usually uses algorithms such as edge detection or Laplace operators to evaluate the detail clarity of the image. The contrast score is calculated based on the difference between light and dark areas in the image, and is determined by analyzing the histogram distribution of the image. High contrast means that the image has obvious light and dark levels. The brightness score involves measuring the average light level of the image, which is obtained by averaging the grayscale values ​​of all pixels. These scores are usually calculated automatically through predefined algorithms and thresholds, providing a basis for quantitative evaluation of image quality.

[0070] For example, a charging station may use a standardized clarity rating scale from 1 to 10. If the edges of the license plate image are accurately identified and there is no obvious blur, it may get a high score, such as 8 or 9. The contrast score may be rated based on the expansion of the image histogram. If the histogram covers a wide range of gray levels, a high contrast score may be obtained. The brightness score may be based on the overall lighting uniformity of the image. If the license plate does not appear overexposed or underexposed in the image, the brightness score will be high.

[0071] S222: Determine an image quality score of the license plate image according to the clarity score, the contrast score, and the brightness score.

[0072] The charging pile will use the clarity, contrast and brightness scores obtained in step S221 to comprehensively determine the image quality score of the license plate image. This comprehensive score may be calculated by weighted average or other mathematical methods, in which each score is given different weights according to its importance to the image quality. For example, clarity may be the most critical for license plate recognition and is therefore given a higher weight. This comprehensive score provides a quantitative measure to evaluate whether the image is suitable for further processing, such as license plate recognition.

[0073] Assuming that the scores of clarity, contrast, and brightness are 8, 6, and 7 respectively, the system may use a weighted average formula (for example, the clarity weight is 0.5, and the contrast and brightness are each 0.25) to calculate the comprehensive score. In this way, the image quality score may be (8*0.5+6*0.25+7*0.25)=7.25.

[0074] S223: Determine the image quality score as the image quality evaluation result.

[0075] This score will be used as a basis for judging whether the license plate image is clear, has sufficient contrast, and is of appropriate brightness. If the comprehensive score reaches or exceeds the preset threshold, the license plate image is considered to be of high quality and can be used for license plate recognition; if the score is below the threshold, further processing may be required, such as cleaning the license plate or reshooting the image.

[0076] For example, if the image quality score threshold is set to 6 and the calculated comprehensive score is 7.25, the image quality assessment result of the license plate image will be determined to be "qualified". If the score is lower than 6, the assessment result may be "unqualified" and the system may recommend cleaning or other operations to improve the image quality.

[0077] S23, judging whether the license plate of the target vehicle is blocked by stains according to the image quality evaluation result.

[0078] The charging station will make a final judgment based on the image quality evaluation results. If the evaluation results show that the image quality is below a certain standard, the charging station will infer that the license plate may be blocked by stains, affecting the clarity, contrast or brightness of the image. In this case, the charging station may trigger the cleaning mechanism, or mark the vehicle's license plate as "unreadable" and take corresponding measures, such as notifying the owner or refusing charging service until the license plate is cleaned and re-identified.

[0079] Step 103: Generate a cleaning control instruction according to the license plate position information of the target vehicle.

[0080] The charging pile needs to accurately calculate the specific location of the license plate, including the relative position and angle between the license plate and the cleaning equipment. The charging pile calculates the specific cleaning path and operating parameters based on the license plate location information, and then integrates the cleaning path and operating parameters into the cleaning control instructions and sends them to the cleaning equipment. Through automated instruction generation, the charging pile can ensure that the cleaning equipment performs the cleaning task according to the established procedures without manual intervention.

[0081] In some embodiments, the above steps may specifically include: (1) According to the license plate position information of the target vehicle, determine the direction angle and distance of the nozzle of the cleaning equipment relative to the license plate.

[0082] The charging pile uses its built-in sensors and image recognition technology to accurately measure the relative position and distance between the license plate and the nozzle of the cleaning equipment. This step involves real-time analysis of the license plate image to determine the exact coordinates of the license plate and its relative direction to the nozzle. The charging pile uses this data to calculate the correct direction and angle that the nozzle needs to be adjusted to directly aim at the license plate for cleaning. This process may also take into account the size and shape of the vehicle to ensure that the nozzle can cover the entire area of ​​the license plate, providing accurate positioning information for the next cleaning operation.

[0083] (2) Determine the spray angle and water pressure of the nozzle based on the direction angle and distance.

[0084] The charging pile takes into account the cleaning efficiency and the safety of the vehicle. First, the setting of the water spray angle ensures that the water flow can be aimed at the license plate in the correct direction. This usually involves adjusting the inclination of the nozzle so that it forms an appropriate angle with the surface of the license plate so that the water flow can cover the entire license plate and effectively remove stains. Secondly, the determination of the water pressure requires a comprehensive consideration of the cleaning effect and the protection of the vehicle. The charging pile will adjust the water pressure according to the distance between the license plate and the nozzle. The farther the distance, the greater the appropriate water pressure may be required to ensure that the water flow can reach and cover the license plate. By precisely controlling the water spray angle and water pressure, the charging pile can ensure that the cleaning process is both efficient and safe, providing the necessary cleaning conditions for accurate license plate recognition.

[0085] (3) Generate cleaning control instructions based on the water spray angle and water pressure.

[0086] Among them, the cleaning control instructions contain a series of specific operation codes to guide the cleaning equipment to perform precise cleaning actions. The charging pile converts the water spray angle and water pressure parameters into specific control signals such as the motor rotation angle and water pump working pressure, and encodes these signals into an instruction format that the cleaning equipment can recognize. Subsequently, the charging pile sends these cleaning control instructions to the cleaning equipment through the communication interface, triggering the cleaning equipment to perform cleaning operations according to the predetermined program. This step is a key link in realizing automated cleaning, ensuring that the cleaning equipment can accurately respond to the instructions of the charging pile and complete the cleaning task of the license plate.

[0087] Step 104: sending the cleaning control instruction to the cleaning device, so that the cleaning device performs a cleaning operation on the license plate of the target vehicle according to the cleaning control instruction.

[0088] The charging pile sends these instructions to the cleaning equipment. After receiving the instructions, the cleaning equipment automatically starts the cleaning program and cleans the license plate of the target vehicle. This process may include a series of automated actions such as spraying water, brushing, and air drying to ensure that the stains on the license plate are completely removed. The design of the cleaning equipment must ensure that the vehicle will not be damaged during the cleaning process, while ensuring the cleaning effect so that the license plate can be accurately identified. The charging pile realizes the automatic cleaning of the license plate obscured by stains by precisely controlling the cleaning equipment, further improving the automation and accuracy of the charging billing process.

[0089] Step 105, after the cleaning device completes the cleaning of the license plate, the second license plate image of the target vehicle is recognized by the license plate recognition model to obtain the second vehicle identity information of the target vehicle.

[0090] After the cleaning equipment completes the cleaning task, the charging pile starts the license plate recognition model again to capture and recognize the license plate of the target vehicle for the second time. This time, since the stains have been removed, the clarity and recognizability of the license plate image are greatly improved, so the confidence of the recognition result can also meet the requirements. The charging pile analyzes the license plate image again through the license plate recognition model, extracts the license plate number, and matches it with the identity information in the database to obtain the accurate second vehicle identity information of the target vehicle.

[0091] This step is the key to ensuring the accuracy of the vehicle’s identity. The charging pile uses intelligent re-identification technology to ensure that vehicle information can be accurately obtained even after cleaning.

[0092] Step 106: Bind the charging billing of the target vehicle with the second vehicle identity information.

[0093] This step ensures that the billing of charging services is directly linked to the identity of the vehicle, avoiding billing errors or confusion. The charging pile uses an intelligent binding mechanism to accurately correspond the vehicle identity information to the charging service. During the charging process of the vehicle, the charging pile monitors the charging status in real time and charges according to the accurate second vehicle identity information. This step not only improves the accuracy of charging billing, but also provides car owners with a clear cost breakdown, ensuring the transparency and fairness of the charging service. Through this process, the charging pile demonstrates its efficient capabilities and intelligence level in automated charging billing.

[0094] The embodiment of the present invention also provides an automatic charging billing method based on identity recognition, referring to Figure 2 , including the following steps: Step 201: After a target vehicle enters a charging parking space, a first license plate image of the target vehicle is recognized by a license plate recognition model to obtain first vehicle identity information of the target vehicle.

[0095] Step 202: When the confidence level of the first vehicle identity information is less than a preset value, determine whether the license plate of the target vehicle is blocked by stains.

[0096] If yes, go to step 203; if no, return to step 201.

[0097] Step 203, generating a cleaning control instruction according to the license plate position information of the target vehicle; Step 204: Send the cleaning control instruction to the cleaning device, so that the cleaning device performs a cleaning operation on the license plate of the target vehicle according to the cleaning control instruction.

[0098] Step 205: After the cleaning device completes the cleaning of the license plate, the second license plate image of the target vehicle is recognized by the license plate recognition model to obtain the second vehicle identity information of the target vehicle.

[0099] The specific contents of steps 201-205 refer to steps 101-105 and will not be repeated here.

[0100] Step 206: Acquire a facial image of the target user in the charging parking space.

[0101] The charging station is equipped with an advanced facial recognition camera. When the target vehicle is parked in the charging parking space, the system automatically activates the camera to capture the driver or user's facial image. This step involves using high-resolution imaging technology and appropriate lighting conditions to ensure that the captured facial image is clear and complete. The system may also use facial detection algorithms to quickly locate and focus on the face area to ensure that the image can be successfully acquired even inside the vehicle.

[0102] For example, when an electric car drives into a parking space, the camera on the charging pile automatically adjusts the angle and focus to capture the driver's frontal facial image. Even if the driver wears glasses or a hat, the system can compensate through a specific algorithm to obtain the best image.

[0103] Step 207: Recognize the face image through a face recognition model to obtain the user identity information of the target user.

[0104] After acquiring the facial image, the charging station uses a built-in or cloud-based facial recognition model to analyze and process the image. The model is trained through deep learning technology and can extract key features from the facial image and match them with the user's facial features stored in the database to identify the user's identity information.

[0105] For example, the system analyzes the feature points of facial images, such as the position and shape of the eyes, nose, and mouth, and compares them with the feature templates in the database to successfully match a specific user and obtain their identity information.

[0106] Step 208, determining whether the user identity information matches the second vehicle identity information.

[0107] Once the facial recognition model provides the user's identity information, the charging station compares this information with the vehicle's second license plate image recognition vehicle identity information. This step ensures the security and accuracy of the charging service and prevents unauthorized use.

[0108] Suppose the face identified by the system belongs to user Zhang San, and the vehicle identified by license plate recognition belongs to Li Si. The system matches Zhang San's identity information with Li Si's vehicle information. If a mismatch is found, further verification may be required or the charging request may be rejected.

[0109] If the user identity information matches the second vehicle identity information, the process proceeds to step 209; otherwise, a prompt message is sent to the user terminal for further confirmation by the user.

[0110] Step 209, start charging and charging for the target vehicle.

[0111] If the user identity information matches the vehicle identity information, the system confirms that the user is authorized to use the vehicle and charge, then starts the charging process and begins billing. This step may involve sending a command to the electrical control unit of the charging station to activate the charging current and record the time and amount of charging started.

[0112] Step 210: Bind the charging billing of the target vehicle with the second vehicle identity information.

[0113] The charging pile binds the charging billing information with the confirmed vehicle identity information to ensure that all charging records can be accurately associated with specific vehicles and users. This helps to improve the transparency of billing, making it easier for users to query charging records and fees, and also facilitates management and settlement by charging station operators.

[0114] The charging pile in this solution is a highly intelligent electric vehicle charging device that integrates advanced license plate recognition technology, automatic cleaning system, face recognition model and intelligent control software. It can automatically detect vehicles entering parking spaces, quickly obtain the first identity information of the vehicle through the license plate recognition model, and automatically determine whether the license plate is blocked by stains when the confidence is insufficient, triggering the cleaning device to clean. After cleaning, the charging pile recognizes the second license plate image of the vehicle again to ensure the accuracy of the vehicle's identity information. In addition, the charging pile is also equipped with a face recognition function to verify the user's identity and match it with the vehicle's identity information, thereby starting the charging billing process. The entire charging process is automated and intelligent, which improves charging efficiency, optimizes user experience, and ensures the accuracy and security of billing by binding charging billing with vehicle identity information.

[0115] The method provided in the above embodiment is executed by a charging pile, which is an electronic device. The following describes the electronic device from the perspective of hardware processing. Figure 3 , is a schematic diagram of a physical device structure of an electronic device in an embodiment of the present invention.

[0116] It should be noted that Figure 3 The structure of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0117] like Figure 3As shown, the electronic device includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In RAM 303, various programs and data required for system operation are also stored. CPU 301, ROM 302 and RAM 303 are connected to each other through bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0118] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0119] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 309, and / or installed from a removable medium 311. When the computer program is executed by a central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0120] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0121] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0122] Specifically, the electronic device of this embodiment includes a processor and a memory, the memory is coupled to one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and one or more processors call the computer instructions to enable the electronic device to execute the method provided by the above embodiment.

[0123] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the electronic device, the electronic device implements the method provided in the above embodiment.

[0124] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

[0125] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0126] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. An automatic charging billing method based on identity recognition, characterized in that: Applied to a charging pile, the method comprises: After the target vehicle enters the charging parking space, a first license plate image of the target vehicle is recognized by a license plate recognition model to obtain first vehicle identity information of the target vehicle; When the confidence level of the first vehicle identity information is less than a preset value, determining whether the license plate of the target vehicle is blocked by stains; If yes, generating a cleaning control instruction according to the license plate position information of the target vehicle; Sending the cleaning control instruction to the cleaning device, so that the cleaning device performs a cleaning operation on the license plate of the target vehicle according to the cleaning control instruction; After the cleaning device completes the cleaning of the license plate, the second license plate image of the target vehicle is recognized by the license plate recognition model to obtain the second vehicle identity information of the target vehicle; The charging billing of the target vehicle is bound to the second vehicle identity information.

2. The method according to claim 1, characterized in that The step of determining whether the license plate of the target vehicle is blocked by stains comprises: Acquiring texture structure information of the license plate image, wherein the texture structure information includes uniformity, roughness and directionality; It is determined whether the license plate of the target vehicle is blocked by stains according to the texture structure information.

3. The method according to claim 1, characterized in that The step of determining whether the license plate of the target vehicle is blocked by stains comprises: Acquire stain features in the license plate image; Determining the proportion of the stain area in the license plate image according to the stain feature; It is determined whether the license plate of the target vehicle is blocked by stains according to the proportion of the stain area.

4. The method according to claim 1, characterized in that: The step of determining whether the license plate of the target vehicle is blocked by stains comprises: Acquiring image quality information of the license plate image, wherein the image quality information includes clarity, contrast and brightness; Determining an image quality assessment result of the license plate image according to the image quality information; Determine whether the license plate of the target vehicle is blocked by stains according to the image quality evaluation result.

5. The method according to claim 4, characterized in that The step of determining the image quality evaluation result of the license plate image according to the image quality information comprises: Respectively obtaining a clarity score, a contrast score, and a brightness score of the license plate image; Determining an image quality score of the license plate image according to the clarity score, the contrast score, and the brightness score; The image quality score is determined as the image quality assessment result.

6. The method according to any one of claims 1 to 5, characterized in that: Before the step of binding the charging billing of the target vehicle with the second vehicle identity information, the method further includes: Acquire a facial image of a target user in the charging parking space; Recognize the face image through a face recognition model to obtain user identity information of the target user; determining whether the user identity information matches the second vehicle identity information; If so, charging and billing will start for the target vehicle.

7. The method according to claim 1, characterized in that The step of generating a cleaning control instruction according to the license plate position information of the target vehicle comprises: According to the license plate position information of the target vehicle, determining the direction angle and distance of the nozzle of the cleaning equipment relative to the license plate; Determine the water spraying angle and water pressure of the nozzle according to the direction angle and distance; A washing control instruction is generated based on the water spray angle and the water pressure.

8. A charging pile, characterized in that: including one or more processors and memory; The memory is coupled to the one or more processors, and the memory is used to store computer program codes, wherein the computer program codes include computer instructions, and the one or more processors call the computer instructions to enable the charging pile to execute the method according to any one of claims 1 to 7.

9. A computer program product comprising instructions, characterized in that When the computer program product runs on a charging pile, the charging pile is enabled to execute the method according to any one of claims 1 to 8.

10. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on the charging pile, the charging pile is caused to execute the method as claimed in any one of claims 1 to 7.

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