Parking lot intelligent fee deduction system

Abstract

The invention discloses an intelligent fee deduction system for a parking lot. The parking lot intelligent fee deduction system comprises the following steps: S10, deploying a high-definition camera and a server, and installing a database for storing vehicle information and image data; s20, when the vehicle enters the parking lot, a camera shoots a vehicle image and extracts feature information; s30, regularly shooting a panoramic image by a camera in the field, and tracking the position change of the vehicle through image comparison; and S40, when the vehicle approaches the exit, shooting the vehicle image again and carrying out feature matching, calculating the parking fee according to the entrance time and the exit time, and completing fee collection through an automatic fee deduction mechanism. The advanced image processing technology and the feature extraction algorithm are used, and the problem that identification is inaccurate under the conditions that license plates are missing, stains exist, and new vehicles do not get on the license plates can be solved; dynamic position tracking of a vehicle in a parking lot can be realized, and parking space management efficiency is improved. An automatic fee deduction mechanism is supported, and the payment efficiency is improved.

Description

Technical Field

[0001] The present invention relates to multiple technical fields such as traffic systems, computer vision, image processing, data management, etc., and in particular to an intelligent parking fee deduction system. Background Art

[0002] The present invention relates to the field of intelligent transportation systems. Existing parking lot management systems usually rely on license plate recognition technology to manage the entry and exit of vehicles and to charge fees. However, in practical applications, license plate recognition faces multiple challenges, including but not limited to: License plate obstruction: When a vehicle enters a parking lot, the license plate will be obstructed, resulting in recognition failure. License plate damage: Stains or damage on the license plate affect the accuracy of recognition. New vehicles without license plates: Newly purchased vehicles have not yet been officially licensed, resulting in the inability to be recognized by the license plate. Environmental factors: Environmental factors such as insufficient light, rainy and snowy weather reduce the accuracy of license plate recognition.

[0003] The current parking management system mainly relies on a single license plate recognition technology, which often leads to inaccurate recognition when encountering the above problems, thus affecting the accuracy of billing. In addition, the existing system often lacks effective vehicle location tracking means and cannot accurately record the movement of vehicles in the parking lot, leading to billing disputes.

[0004] In view of the problems existing in the prior art, the present invention aims to provide an intelligent parking fee deduction system, which can accurately identify vehicles in a variety of situations and ensure that vehicles can be accurately identified and parking fees can be calculated even in the case of missing license plates, stains, or new cars without license plates through the comprehensive use of multiple features. Summary of the invention

[0005] The present invention provides a method for implementing a parking lot intelligent fee deduction system, comprising:

[0006] S10, deploy high-definition cameras and servers, and install a database for storing vehicle information and image data;

[0007] S20, when the vehicle enters the parking lot, the camera captures the vehicle image and extracts feature information;

[0008] S30, the cameras in the field regularly capture panoramic images and track the position changes of vehicles through image comparison;

[0009] S40: When the vehicle approaches the exit, the vehicle image is captured again and feature matching is performed, the parking fee is calculated based on the entry and exit time, and the fee is collected through an automatic deduction mechanism.

[0010] A method for implementing the parking lot intelligent fee deduction system as described above, wherein a high-definition camera and a server are deployed, and a database is installed to store vehicle information and image data, including the following sub-steps:

[0011] Install high-definition cameras at the parking lot entrance, exit and key locations within the lot;

[0012] Configure the server to support image processing and data storage, and establish a database for storing vehicle information and image data;

[0013] Install image processing and data analysis software;

[0014] Set the initial parameters of the image processing algorithm, such as threshold, feature extraction method, etc.

[0015] The method for implementing the parking lot intelligent fee deduction system as described above, wherein when a vehicle enters the parking lot, a camera captures an image of the vehicle and extracts feature information, comprises the following sub-steps:

[0016] When a vehicle enters the parking lot, the camera captures the front image of the vehicle;

[0017] Use image processing algorithms to extract features such as license plate number, body color, and model, and save this information along with a timestamp into a database;

[0018] A profile is created for each vehicle, recording entry time and characteristics.

[0019] A method for implementing the parking lot intelligent fee deduction system as described above, wherein a camera in the parking lot regularly captures a panoramic image and tracks the position changes of vehicles through image comparison, comprises the following sub-steps:

[0020] The cameras in the venue capture panoramic images at set time intervals (e.g., every 5 minutes);

[0021] Use image processing algorithms to compare old and new images to detect whether a vehicle has moved or left;

[0022] If a change in the vehicle's position is detected, the vehicle's current position information is updated;

[0023] For each location update, the specific location coordinates of the vehicle are recorded.

[0024] A method for implementing a parking lot intelligent fee deduction system as described above, wherein when a vehicle approaches an exit, the vehicle image is captured again and feature matching is performed, the parking fee is calculated based on the entry and exit time, and the fee is collected through an automatic fee deduction mechanism, including the following sub-steps:

[0025] When the vehicle approaches the exit, the camera captures the vehicle image again;

[0026] Use feature matching algorithms to confirm whether the information of vehicles leaving the site is consistent with that of vehicles entering the site;

[0027] Query the entry time and location information in the database based on vehicle characteristics;

[0028] The parking time is calculated based on the entry and exit time, and the parking fee is calculated according to the billing rules;

[0029] Complete automatic deductions through the preset payment interface.

[0030] The present invention also provides a parking lot intelligent fee deduction system, comprising:

[0031] System deployment and initialization module: deploy high-definition cameras and servers in the parking lot, and install a database to store vehicle information and image data;

[0032] Vehicle entry recognition module: When a vehicle enters the parking lot, the camera captures the vehicle image and extracts feature information, including license plate number, vehicle model, color, etc., and stores it in the database together with the entry time;

[0033] Vehicle location tracking module: The cameras in the field regularly capture panoramic images and track vehicle location changes through image comparison, and update the vehicle's current location information;

[0034] Vehicle exit processing module: When the vehicle approaches the exit, the vehicle image is captured again and feature matching is performed. The parking fee is calculated based on the entry and exit time, and the fee is collected through an automatic deduction mechanism.

[0035] A parking lot intelligent fee deduction system as described above, wherein the system deployment and initialization module deploys a high-definition camera and a server, and installs a database for storing vehicle information and image data, including:

[0036] Deploy cameras: Install high-definition cameras at the entrance and exit of the parking lot and key locations within the lot;

[0037] Set up the server and database: configure the server to support image processing and data storage and establish a database to store vehicle information and image data;

[0038] Install necessary software: Install image processing and data analysis software to ensure the system can run efficiently;

[0039] Initialize system parameters: set the parameters of the image processing algorithm, such as threshold, feature extraction method, etc.

[0040] In the above-mentioned parking lot intelligent fee deduction system, the vehicle entry recognition module, i.e., when a vehicle enters the parking lot, the camera captures the vehicle image and extracts feature information, includes:

[0041] Capture entry image: When the vehicle arrives at the entrance, the camera captures the front image of the vehicle;

[0042] Feature extraction and storage: Use image processing algorithms to extract features such as license plate number, body color, and vehicle model, and save this information together with the timestamp into the database;

[0043] Create vehicle profiles: Create a profile for each vehicle, recording entry time and feature information.

[0044] In the above-mentioned parking lot intelligent fee deduction system, the vehicle position tracking module, i.e., the camera in the parking lot regularly captures panoramic images and tracks the vehicle position changes through image comparison, comprises:

[0045] Regularly capture panoramic images: The cameras in the venue capture panoramic images at set time intervals (e.g., every 5 minutes);

[0046] Image comparison and analysis: Use image processing algorithms to compare old and new images to detect whether a vehicle has moved or left;

[0047] Update vehicle position: If a change in the vehicle position is detected, update the vehicle's current position information;

[0048] Record vehicle trajectory: For each location update, record the specific location coordinates of the vehicle.

[0049] In the above-mentioned parking lot intelligent fee deduction system, the vehicle exit processing module, when the vehicle approaches the exit, takes the vehicle image again and performs feature matching, calculates the parking fee according to the entry and exit time, and completes the fee collection through the automatic deduction mechanism, including:

[0050] Capture exit image: When the vehicle approaches the exit, the camera captures the vehicle image again;

[0051] Feature matching to confirm vehicle: Use feature matching algorithm to confirm whether the information of the vehicle leaving the venue is consistent with that when entering the venue;

[0052] Query parking information: query the entry time and location information in the database based on vehicle characteristics;

[0053] Calculate parking fees: calculate parking duration based on entry and exit times, and calculate parking fees based on billing rules;

[0054] Automatic deduction: Automatic deduction is completed through the preset payment interface.

[0055] The beneficial effects achieved by the present invention are as follows: the present invention can improve the accuracy of vehicle identification and billing, optimize parking lot management processes, enhance user experience, and reduce operating costs by comprehensively using a variety of technical means. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0057] Figure 1 This is a flow chart of a parking lot intelligent fee deduction system provided in Example 1 of the present application;

[0058] Figure 2 It is a schematic diagram of a parking lot intelligent fee deduction system provided in Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0059] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0060] Embodiment 1

[0061] like Figure 1 As shown, the first embodiment of the present application provides a method for implementing a parking lot intelligent fee deduction system, including:

[0062] Step S10: deploying high-definition cameras and servers, and installing a database for storing vehicle information and image data;

[0063] By deploying cameras and servers, installing software and setting initial parameters, we can ensure that the parking fee deduction system can operate normally and efficiently, including the following sub-steps:

[0064] Step S11: deploying high-definition cameras and servers in the parking lot, and installing a database for storing vehicle information and image data;

[0065] Choose the appropriate HD camera model based on the size and lighting conditions of the parking lot; determine the installation location, and determine the best installation location for the camera at the entrance, exit, and key locations within the parking lot; install the camera and adjust the angle to ensure coverage of the required area; test the camera to ensure that the camera is working properly and the image is clear and unobstructed.

[0066] Step S12: configuring the server to support image processing and data storage and establishing a database for storing vehicle information and image data;

[0067] Select a suitable server based on the expected data processing volume and storage requirements; install the operating system, configure network settings, set firewall rules, etc.; select a suitable database management system (such as MySQL, PostgreSQL, etc.) and install it; design the database structure and create the necessary tables and fields to store vehicle information and image data.

[0068] Step S13: Install image processing and data analysis software to ensure that the system can run efficiently;

[0069] Select appropriate image processing software (such as OpenCV) and data analysis tools (such as Python, R, etc.); install these software on the server and ensure that all necessary dependencies are installed; configure the software's working directory, set the software's working directory, environment variables, etc.

[0070] Step S14: setting parameters of the image processing algorithm, such as threshold, feature extraction method, etc.;

[0071] Set the parameters of the image processing algorithm, such as thresholds, feature extraction methods, etc., based on factors such as camera characteristics and lighting conditions; use a test image set to verify the effect of the parameter settings and make adjustments based on the results.

[0072] Step S20: When a vehicle enters the parking lot, the camera captures the vehicle image and extracts feature information, including the license plate number, vehicle model, color, etc., and stores it in the database together with the entry time, including the following steps:

[0073] Step S21: When the vehicle arrives at the entrance, the camera captures the front image of the vehicle;

[0074] When a vehicle arrives at the entrance, the camera is started through a sensor or other trigger mechanism; the camera angle is adjusted to ensure that the camera can capture the front of the vehicle so as to clearly capture the license plate and other features; the camera exposure, gain and other settings are adjusted to ensure high-quality images under different lighting conditions; the captured images are saved to a specified folder or database on the server.

[0075] Step S22: using image processing algorithms to extract features such as the license plate number, body color, and vehicle model, and saving this information together with a timestamp into a database;

[0076] Use a license plate recognition algorithm to extract the license plate number from the image; use a color analysis algorithm to determine the main color of the vehicle body; use a deep learning model or other image classification technology to identify the model of the vehicle; save the license plate number, body color, model and other information together with the timestamp into the database.

[0077] Step S23: Create a file for each vehicle, recording the entry time and feature information;

[0078] Generate a unique identifier (e.g., UUID) for each vehicle as a profile ID; record the exact time the vehicle enters the parking lot; associate feature information such as license plate number, body color, and vehicle model with the vehicle profile ID; store the vehicle profile information in a database, including the profile ID, entry time, and all extracted feature information.

[0079] Step S30: The camera in the field regularly captures panoramic images and tracks the position changes of the vehicle through image comparison, and updates the current position information of the vehicle, including the following sub-steps;

[0080] Step S31: The on-site camera captures a panoramic image at a set time interval (e.g., every 5 minutes);

[0081] Configure the camera to take pictures at a scheduled time, for example, take a panoramic image every 5 minutes; adjust the camera angle to ensure that the camera can cover the entire parking area so as to capture the positions of all vehicles; adjust the camera settings, such as exposure and resolution, to ensure that the image clarity is suitable for subsequent image processing; save the captured panoramic image to a server or database.

[0082] Step S32: Use an image processing algorithm to compare the new and old images to detect whether a vehicle has moved or left.

[0083] Use image processing algorithms (such as SIFT, SURF or ORB, etc.) to extract key feature points from the image; detect the position change of the vehicle by comparing the difference in feature points between the newly captured image and the most recently captured image; based on the feature matching results, determine which vehicles have moved. If a vehicle no longer appears in the new image, it can be considered that the vehicle has left.

[0084] Step S33: if a change in the vehicle position is detected, the current position information of the vehicle is updated;

[0085] Based on the position information of the feature points, the position coordinates of the vehicle in the image are calculated, and the new position coordinates of the vehicle are updated to the vehicle file. If it is detected that the vehicle has left, its status is updated to "left".

[0086] Step S34: For each location update, the specific location coordinates of the vehicle are recorded.

[0087] Create a track record for each vehicle, including the specific coordinates of each position update;

[0088] Step S35: Based on the accuracy of the alarm and changes in the market environment, continuously calculate and adjust the model parameters and threshold settings to optimize the performance of the anomaly detection system; store the trajectory information in the database, including timestamps, location coordinates and other information; maintain historical trajectory records over a period of time so that the historical location information of the vehicle can be queried when needed.

[0089] Step S40: When the vehicle approaches the exit, the vehicle image is captured again and feature matching is performed, the parking fee is calculated based on the entry and exit time, and the fee is collected through the automatic deduction mechanism, including the following sub-steps:

[0090] Step S41: When the vehicle approaches the exit, the camera captures the vehicle image again;

[0091] When a vehicle approaches an exit, start the camera shooting through a sensor or other trigger mechanism; ensure that the camera can capture the front of the vehicle so that the license plate and other features are clearly captured; adjust the camera's exposure, gain and other settings to ensure high-quality images under different lighting conditions; save the captured images to a specified folder or database on the server.

[0092] Step S42: Use a feature matching algorithm to confirm whether the information of the vehicle leaving the venue is consistent with that of the vehicle entering the venue;

[0093] Use a license plate recognition algorithm to extract the license plate number from the image; use a color analysis algorithm to determine the main color of the vehicle body; use a deep learning model or other image classification technology to identify the model of the vehicle; match the license plate number, body color, model and other information in the exit image with the information recorded at the time of entry; if the match is successful, it is confirmed that the vehicle is the same vehicle.

[0094] Step S43: querying the entry time and location information in the database according to the vehicle characteristics;

[0095] According to the result of feature matching, the file of the vehicle is searched in the database; the entry time is extracted from the vehicle file; and the location information at the time of entry is extracted from the vehicle file.

[0096] Step S44: Calculate the parking duration according to the entry and exit time, and calculate the parking fee according to the charging rules;

[0097] Calculate the total parking time based on the entry time and the current time; calculate the parking fee based on the parking lot's billing standards (such as hourly charges, daily charges, etc.); determine the final parking fee to be paid after considering any discounts or preferential policies.

[0098] Step S45: Complete automatic deduction through the preset payment interface.

[0099] Obtain the preset payment method information from the vehicle file; complete automatic deduction through the preset payment interface (such as bank API or third-party payment platform); update the payment status of the vehicle file in the database; send a confirmation message of successful payment to the owner.

[0100] Embodiment 2

[0101] like Figure 2 As shown, the second embodiment of the present application provides a parking lot intelligent fee deduction system, including:

[0102] System deployment and initialization module 21: deploy high-definition cameras and servers, and install a database for storing vehicle information and image data;

[0103] By deploying cameras and servers, installing software and setting initial parameters, we ensure that the parking fee deduction system can operate normally and efficiently, including:

[0104] 1. Deploy high-definition cameras and servers in the parking lot, and install a database to store vehicle information and image data;

[0105] Choose the appropriate HD camera model based on the size and lighting conditions of the parking lot; determine the installation location, and determine the best installation location for the camera at the entrance, exit, and key locations within the parking lot; install the camera and adjust the angle to ensure coverage of the required area; test the camera to ensure that the camera is working properly and the image is clear and unobstructed.

[0106] 2. Configure the server to support image processing and data storage and establish a database for storing vehicle information and image data;

[0107] Select a suitable server based on the expected data processing volume and storage requirements; install the operating system, configure network settings, set firewall rules, etc.; select a suitable database management system (such as MySQL, PostgreSQL, etc.) and install it; design the database structure and create the necessary tables and fields to store vehicle information and image data.

[0108] 3. Install image processing and data analysis software to ensure the system can run efficiently;

[0109] Select appropriate image processing software (such as OpenCV) and data analysis tools (such as Python, R, etc.); install these software on the server and ensure that all necessary dependencies are installed; configure the software's working directory, set the software's working directory, environment variables, etc.

[0110] 4. Set the parameters of the image processing algorithm, such as threshold, feature extraction method, etc.;

[0111] Set the parameters of the image processing algorithm, such as thresholds, feature extraction methods, etc., based on factors such as camera characteristics and lighting conditions; use a test image set to verify the effect of the parameter settings and make adjustments based on the results.

[0112] Vehicle entry recognition module 22: When a vehicle enters the parking lot, the camera captures the vehicle image and extracts feature information, including license plate number, vehicle model, color, etc., and stores it in the database together with the entry time, including:

[0113] 1. When the vehicle arrives at the entrance, the camera captures the front image of the vehicle;

[0114] When a vehicle arrives at the entrance, the camera is started through a sensor or other trigger mechanism; the camera angle is adjusted to ensure that the camera can capture the front of the vehicle so as to clearly capture the license plate and other features; the camera exposure, gain and other settings are adjusted to ensure high-quality images under different lighting conditions; the captured images are saved to a specified folder or database on the server.

[0115] 2. Use image processing algorithms to extract features such as license plate number, body color, and model, and save this information together with the timestamp into the database;

[0116] Use a license plate recognition algorithm to extract the license plate number from the image; use a color analysis algorithm to determine the main color of the vehicle body; use a deep learning model or other image classification technology to identify the model of the vehicle; save the license plate number, body color, model and other information together with the timestamp into the database.

[0117] 3. Create a file for each vehicle, recording the entry time and characteristic information;

[0118] Generate a unique identifier (e.g., UUID) for each vehicle as a profile ID; record the exact time the vehicle enters the parking lot; associate feature information such as license plate number, body color, and vehicle model with the vehicle profile ID; store the vehicle profile information in a database, including the profile ID, entry time, and all extracted feature information.

[0119] Vehicle location tracking module 23: The cameras in the field regularly capture panoramic images and track vehicle location changes through image comparison, and update the current location information of the vehicle, including:

[0120] 1. The cameras in the venue take panoramic images at set time intervals (e.g. every 5 minutes);

[0121] Configure the camera to take pictures at a scheduled time, for example, take a panoramic image every 5 minutes; adjust the camera angle to ensure that the camera can cover the entire parking area so as to capture the positions of all vehicles; adjust the camera settings, such as exposure and resolution, to ensure that the image clarity is suitable for subsequent image processing; save the captured panoramic image to a server or database.

[0122] 2. Use image processing algorithms to compare old and new images to detect whether a vehicle has moved or left;

[0123] Use image processing algorithms (such as SIFT, SURF or ORB, etc.) to extract key feature points from the image; detect the position change of the vehicle by comparing the difference in feature points between the newly captured image and the most recently captured image; based on the feature matching results, determine which vehicles have moved. If a vehicle no longer appears in the new image, it can be considered that the vehicle has left.

[0124] 3. If the vehicle position is detected to have changed, the vehicle's current position information is updated;

[0125] Based on the position information of the feature points, the position coordinates of the vehicle in the image are calculated, and the new position coordinates of the vehicle are updated to the vehicle file. If it is detected that the vehicle has left, its status is updated to "left".

[0126] 4. For each location update, record the specific location coordinates of the vehicle;

[0127] Create a track record for each vehicle, including the specific coordinates of each position update;

[0128] 5. Continuously calculate and adjust model parameters and threshold settings based on the accuracy of the alarm and changes in the market environment to optimize the performance of the anomaly detection system; store trajectory information in the database, including timestamps, location coordinates, etc.; maintain historical trajectory records over a period of time so that the vehicle's historical location information can be queried when needed.

[0129] Vehicle exit processing module 24: When the vehicle approaches the exit, the vehicle image is captured again and feature matching is performed, the parking fee is calculated based on the entry and exit time, and the fee is collected through an automatic deduction mechanism, including;

[0130] 1. When the vehicle approaches the exit, the camera captures the vehicle image again;

[0131] When a vehicle approaches an exit, start the camera shooting through a sensor or other trigger mechanism; ensure that the camera can capture the front of the vehicle so that the license plate and other features are clearly captured; adjust the camera's exposure, gain and other settings to ensure high-quality images under different lighting conditions; save the captured images to a specified folder or database on the server.

[0132] 2. Use feature matching algorithm to confirm whether the information of the vehicle leaving the venue is consistent with that of the vehicle entering the venue;

[0133] Use a license plate recognition algorithm to extract the license plate number from the image; use a color analysis algorithm to determine the main color of the vehicle body; use a deep learning model or other image classification technology to identify the model of the vehicle; match the license plate number, body color, model and other information in the exit image with the information recorded at the time of entry; if the match is successful, it is confirmed that the vehicle is the same vehicle.

[0134] 3. Query the entry time and location information in the database based on vehicle characteristics;

[0135] According to the result of feature matching, the file of the vehicle is searched in the database; the entry time is extracted from the vehicle file; and the location information at the time of entry is extracted from the vehicle file.

[0136] 4. Calculate the parking time based on the entry and exit time, and calculate the parking fee according to the charging rules;

[0137] Calculate the total parking time based on the entry time and the current time; calculate the parking fee based on the parking lot's billing standards (such as hourly charges, daily charges, etc.); determine the final parking fee to be paid after considering any discounts or preferential policies.

[0138] 5. Complete automatic deduction through the preset payment interface.

[0139] Obtain the preset payment method information from the vehicle file; complete automatic deduction through the preset payment interface (such as bank API or third-party payment platform); update the payment status of the vehicle file in the database; send a confirmation message of successful payment to the owner.

Claims

1. A method for implementing a parking lot intelligent fee deduction system, characterized in that: include: S10, deploy high-definition cameras and servers, and install a database for storing vehicle information and image data; S20, when the vehicle enters the parking lot, the camera captures the vehicle image and extracts feature information; S30, the cameras in the field regularly capture panoramic images and track the position changes of vehicles through image comparison; S40: When the vehicle approaches the exit, the vehicle image is captured again and feature matching is performed, the parking fee is calculated based on the entry and exit time, and the fee is collected through an automatic deduction mechanism.

2. A method for implementing a parking lot intelligent fee deduction system as claimed in claim 1, characterized in that: Deploy high-definition cameras and servers, and install a database to store vehicle information and image data, including the following sub-steps: Install high-definition cameras at the parking lot entrance, exit and key locations within the lot; Configure the server to support image processing and data storage, and establish a database for storing vehicle information and image data; Install image processing and data analysis software; Set the initial parameters of the image processing algorithm, such as threshold, feature extraction method, etc.

3. The method for implementing a parking lot intelligent fee deduction system according to claim 1, characterized in that: When a vehicle enters the parking lot, the camera captures the vehicle image and extracts feature information, including the following sub-steps: When a vehicle enters the parking lot, the camera captures the front image of the vehicle; Use image processing algorithms to extract features such as license plate number, body color, and model, and save this information along with a timestamp into a database; A profile is created for each vehicle, recording entry time and characteristics.

4. A method for implementing a parking lot intelligent fee deduction system as claimed in claim 1, characterized in that: The cameras in the field regularly capture panoramic images and track the position changes of vehicles through image comparison, including the following sub-steps: The cameras in the venue capture panoramic images at set time intervals (e.g., every 5 minutes); Use image processing algorithms to compare old and new images to detect whether a vehicle has moved or left; If a change in the vehicle's position is detected, the vehicle's current position information is updated; For each location update, the specific location coordinates of the vehicle are recorded.

5. The method for implementing a parking lot intelligent fee deduction system according to claim 1, characterized in that: When the vehicle approaches the exit, the vehicle image is captured again and feature matching is performed. The parking fee is calculated based on the entry and exit time, and the fee is collected through an automatic deduction mechanism, including the following sub-steps: When the vehicle approaches the exit, the camera captures the vehicle image again; Use feature matching algorithms to confirm whether the information of vehicles leaving the site is consistent with that of vehicles entering the site; Query the entry time and location information in the database based on vehicle characteristics; The parking time is calculated based on the entry and exit time, and the parking fee is calculated according to the billing rules; Complete automatic deductions through the preset payment interface.

6. A parking lot intelligent fee deduction system, characterized in that: include: System deployment and initialization module: deploy high-definition cameras and servers in the parking lot, and install a database to store vehicle information and image data; Vehicle entry recognition module: When a vehicle enters the parking lot, the camera captures the vehicle image and extracts feature information, including license plate number, vehicle model, color, etc., and stores it in the database together with the entry time; Vehicle location tracking module: The cameras in the field regularly capture panoramic images and track vehicle location changes through image comparison, and update the vehicle's current location information; Vehicle exit processing module: When the vehicle approaches the exit, the vehicle image is captured again and feature matching is performed. The parking fee is calculated based on the entry and exit time, and the fee is collected through an automatic deduction mechanism.

7. The parking lot intelligent fee deduction system as claimed in claim 6, characterized in that:The system deployment and initialization module deploys high-definition cameras and servers, and installs a database to store vehicle information and image data, including: Deploy cameras: Install high-definition cameras at the entrance and exit of the parking lot and key locations within the lot; Set up server and database: configure the server to support image processing and data storage and establish a database to store vehicle information and image data; Install necessary software: Install image processing and data analysis software to ensure the system can run efficiently; Initialize system parameters: set the parameters of the image processing algorithm, such as threshold, feature extraction method, etc.

8. The parking lot intelligent fee deduction system as claimed in claim 6, characterized in that: The vehicle entry recognition module is when a vehicle enters the parking lot, the camera captures the vehicle image and extracts feature information, including: Capture entry image: When the vehicle arrives at the entrance, the camera captures the front image of the vehicle; Feature extraction and storage: Use image processing algorithms to extract features such as license plate number, body color, and vehicle model, and save this information together with the timestamp into the database; Create vehicle profiles: Create a profile for each vehicle, recording entry time and feature information.

9. The parking lot intelligent fee deduction system as claimed in claim 6, characterized in that: The vehicle position tracking module is a camera in the field that regularly captures panoramic images and tracks vehicle position changes through image comparison, including: Regularly capture panoramic images: The cameras in the venue capture panoramic images at set time intervals (e.g., every 5 minutes); Image comparison and analysis: Use image processing algorithms to compare old and new images to detect whether a vehicle has moved or left; Update vehicle position: If a change in the vehicle position is detected, update the vehicle's current position information; Record vehicle trajectory: For each location update, record the specific location coordinates of the vehicle.

10. The parking lot intelligent fee deduction system as claimed in claim 6, characterized in that: The vehicle exit processing module takes another photo of the vehicle and performs feature matching when the vehicle approaches the exit. The parking fee is calculated based on the entry and exit time, and the fee is collected through an automatic deduction mechanism, including: Capture exit image: When the vehicle approaches the exit, the camera captures the vehicle image again; Feature matching to confirm vehicle: Use feature matching algorithm to confirm whether the information of the vehicle leaving the venue is consistent with that when entering the venue; Query parking information: query the entry time and location information in the database based on vehicle characteristics; Calculate parking fees: calculate parking duration based on entry and exit times, and calculate parking fees based on billing rules; Automatic deduction: Automatic deduction is completed through the preset payment interface.

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