How to realize license plate recognition from principle to application

In the process of rapid growth of urban vehicles, how to achieve effective management of vehicles has become an important factor in testing the transportation sector. As early as in the Shenzhen Municipal Public Security Bureau's "Parking (field) vehicle image and number plate information collection and transmission system technical requirements", license plate recognition technology has become the main means of vehicle identification. So, how is the license plate recognition technology implemented? What are the main application scenarios?

从原理到应用,车牌识别如何实现

Implementation of license plate recognition

The license plate recognition system has two trigger modes, one is peripheral trigger and the other is video trigger.

The peripheral triggering mode refers to detecting the vehicle passing signal by coil, infrared or other detectors. After the license plate recognition system receives the vehicle trigger signal, it collects the vehicle image, automatically recognizes the license plate, and performs subsequent processing. The method has the advantages of high triggering rate and stable performance; the disadvantage is that the coil is required to be cut on the ground, and the construction amount is large.

The video triggering method refers to the license plate recognition system adopting the dynamic moving target sequence image analysis processing technology to detect the moving condition of the vehicle on the lane in real time, and find that the vehicle image is captured when the vehicle passes, the license plate is recognized, and the subsequent processing is performed. Video triggering does not require coils, infrared or other hardware vehicle detectors. The method has the advantages of convenient construction, no need to cut the ground to lay the coil, and does not need to install parts such as the vehicle inspection device, but its disadvantages are also very significant. Due to the limitation of the algorithm, the trigger rate and the recognition rate of the scheme are set outside. The trigger is much lower.

从原理到应用,车牌识别如何实现

1) Indirect method: means to identify the license plate and related information by identifying the information of the license plate stored in the IC card or barcode installed in the car. IC card technology has high recognition accuracy, reliable operation and can work all day, but its whole set of equipment is expensive, hardware equipment is very complicated, and it is not suitable for off-site operation. Bar code technology has fast recognition speed, high accuracy, high reliability and cost. Low-end advantages, but high requirements for the scanner. In addition, both need to develop a unified national standard, and it is impossible to check whether the car and the barcode are consistent. It is also a technical shortcoming, which makes it difficult to promote in a short period of time.

2) Direct method: Image-based license plate recognition technology is a direct method, which is a passive type license plate intelligent identification method, which can be used for a moving state vehicle or a stationary state vehicle without any vehicle-mounted transmitting device that transmits a license plate signal. The license plate number is used for non-contact information collection and real-time intelligent identification. Compared with the indirect method identification system, first of all, this system saves equipment placement and a large amount of funds, thereby improving economic efficiency. Secondly, due to the adoption of advanced computer application technology, the recognition speed can be improved and the real-time performance can be better solved. The problem; again, it is identified based on the image, so the recognition error in the system can be solved by human participation, and other methods are difficult to interact with people.

Framework process for license plate recognition

The license plate recognition system adopts a highly modular design, and each part of the license plate recognition process is used as a separate module. The system framework is as follows.

1. Vehicle detection and tracking module

The vehicle detection and tracking module mainly analyzes the video stream, determines the position of the vehicle, tracks the vehicle in the image, and records the close-up picture of the vehicle at the best moment of the vehicle position. The system can be well received by adding the tracking module. The ground overcomes various external disturbances, so that a more reasonable recognition result can detect unlicensed vehicles and output the results.

2, license plate positioning module

The license plate location module is a very important link and the basis of the follow-up link. Its accuracy has a great impact on the overall system performance. The license plate system completely abandons the previous algorithm and realizes a new license plate location algorithm based on learning and multiple feature fusion, which is suitable for various complex background environments and different camera angles.

3, license plate correction and fine positioning module

Due to the limitation of shooting conditions, the license plate in the image always has a certain inclination, and a correction and fine positioning link is needed to further improve the quality of the license plate image and prepare for the segmentation and recognition module. Using a well-designed fast image processing filter, not only is the calculation fast, but also the overall information of the license plate is used to avoid the influence of local noise. Another advantage of using this algorithm is that it can also fine-tune the license plate by analyzing multiple intermediate results, further reducing the impact of non-licence areas.

4, license plate segmentation module

The license plate segmentation module of the license plate system utilizes various features such as grayscale, color, and edge distribution of the license plate text, which can better suppress the influence of other noises around the license plate and can tolerate license plates with a certain inclination angle. This algorithm is useful for applications such as mobile inspections where the license plate image is noisy.

5, license plate recognition module

In the license plate recognition system, a combination of multiple recognition models is usually used to identify the license plate, and a hierarchical character recognition process is constructed, which can effectively improve the correct rate of character recognition. On the other hand, before the character recognition, the computer intelligent algorithm is used to pre-process the character image, which not only preserves the image information as much as possible, but also improves the image quality, improves the distinguishability of similar characters, and ensures the reliability of character recognition.

6, the license plate recognition result decision module

The recognition result decision module, specifically, the decision module utilizes the history records left by the process of the license plate passing through the field of view to make an intelligent decision on the recognition result. It obtains the comprehensive credibility evaluation of the license plate by calculating the number of observation frames, the stability of the recognition result, the trajectory stability, the speed stability, the average credibility and the similarity, thereby determining whether to continue tracking the license plate or output. Identify the result or reject the result. This method comprehensively utilizes the information of all frames, reduces the contingency error caused by the previous single image based recognition algorithm, and greatly improves the recognition rate and the correctness and reliability of the recognition result.

7, license plate tracking module

The license plate tracking module records various historical information such as the position, appearance, recognition result, credibility and the like of the license plate in each frame of the vehicle during driving. Since the license plate tracking module adopts a motion model with a certain fault tolerance and an updated model, those license plates that are short-time occluded or instantaneously blurred can still be correctly tracked and predicted, and finally only one recognition result is output.

8, online learning module

In each of the above modules, a large number of learning-based algorithms are used. The system adds an online learning module, adopts the latest feedback learning model, and uses the decision-making module and the tracking module to obtain feedback information such as license plate quality, vehicle trajectory and speed. Some algorithm parameters are updated to make the system adapt to the new application environment quickly. As a powerful complement to existing algorithms, this algorithm will further improve system performance.

Application scenario

Monitoring alarm

For vehicles that are included in the “blacklist”, such as vehicles that are wanted or lost, vehicles that are underpaid, vehicles that are not inspected, accidents, and illegal vehicles, simply enter their license plate number into the application system, and license plate identification equipment is installed. At the designated intersection, bayonet or by law enforcement personnel, it will be placed as needed. The system will read all the license plate numbers of the passing vehicles and compare them with the “blacklist” in the system. Once the designated vehicle is found, it will immediately send out an alarm message.

Speeding violation punishment

The license plate recognition technology combined with the speed measuring device can be used for vehicle speeding violation punishment, generally used for highways. The specific application is: set the speed monitoring point on the road, capture the speeding vehicle and identify the license plate number, send the license number and picture of the illegal vehicle to each exit; set the penalty point at each exit, identify the passing vehicle and the number with the license plate recognition device Compared with the number of overspeed vehicles that have been received, once the numbers are the same, the warning device is activated to notify the law enforcement personnel to handle the problem.

Vehicle access management

The license plate recognition device is installed at the entrance and exit, the license plate number and the entry and exit time of the vehicle are recorded, and combined with the control devices of the automatic door and the railing machine to realize automatic management of the vehicle. It can be used in the parking lot to realize automatic timing charging. It can also automatically calculate the number of available parking spaces and give tips. The automatic management of parking charges can save manpower and improve efficiency. The application to the intelligent community can automatically determine whether the entering vehicle belongs to the local area, and realize automatic time charging for non-internal vehicles. In some units, this application can also be combined with the vehicle dispatching system to automatically and objectively record the vehicle out of the unit. The license plate recognition management system uses the license plate recognition technology to achieve no parking, no card, and effectively improve the vehicle. Access efficiency.

从原理到应用,车牌识别如何实现

Highway toll management

Vehicle license plate recognition equipment is installed at each entrance and exit of the expressway. When the vehicle enters, the vehicle license plate is identified to store the entry data into the toll collection system. When the vehicle arrives at the exit, the license plate is re-identified and the entry information is invoked according to the license information, and the charge management is implemented in conjunction with the entry and exit data. This application enables automatic billing and prevents cheating, avoiding the loss of receivables.

The expressway has begun to implement network charging. With the expansion of the network, the difference between the different models is getting higher and higher. The problem of drivers using the existing charging system to evade fees through mid-way card replacement will become more and more prominent. License plate recognition technology is the fundamental way to solve such problems.

Calculate vehicle travel time

In the traffic management system, the average travel time of the vehicle on a certain road can be used as a parameter for judging the road congestion condition. Install the license plate recognition device at the starting and ending point of the road, read all passing vehicles and transfer the license plate number back to the traffic command center. The management system of the command center can calculate the average travel time of the vehicle based on these results.

Automatic registration of license plate numbers

The license plate recognition parking lot management system automatically recognizes and converts the vehicle license plate number image taken by the camera at the entrance into a digital signal. To achieve one card and one car, the advantage of license plate recognition is that the card and the car can be matched to improve the management. The advantage of the card and the car is that the long-term card must be used together with the car to prevent the use of one card and multiple cars. Vulnerabilities to improve the efficiency of property management; at the same time automatically compare the entry and exit of vehicles to prevent theft. The upgraded camera system can capture clearer pictures and save them as files, which can provide strong evidence for some disputes. It is convenient for managers to compare when the vehicle is on the scene, which greatly enhances the security of the system.

In addition, today, with the rapid growth of urban population, the rapid increase in vehicle ownership and the implementation of government regulations, the electronic toll collection system is expected to drive the growth of the license plate recognition market. According to the survey, in the Asia-Pacific region, the license plate recognition system will grow at a rate of 18.06% (higher than the highest in other regions), responding to the current rapid growth in traffic congestion, police enforcement, fees and parking lots.

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