With the rapid increase in the number of vehicles due to the development of the social economy, there is an ever-growing demand for reasonable traffic control and toll management. Utilizing electronic information technology to achieve stable and intelligent traffic has become the main development direction for traffic management. As an integral part of urban development, the smart city is rising and accelerating in major cities. Intelligent Transportation Systems (ITS) are the primary focus of vehicle control and management systems, with vehicle license plates, or simply plate numbers, serving as identifiers for vehicle identity. Plate recognition systems are used for automatic registration and verification of vehicle identities, ensuring consistency. Therefore, plate recognition systems are now an essential component of intelligent transportation systems. Currently, the main application of plate recognition systems in intelligent transportation is in the intelligent monitoring and recording of road vehicles, used for automatically recording violations such as running red lights, illegal left turns, lane violations, going against traffic, and speeding. This indexing of vehicle and driver records facilitates traffic management and enforcement, and can extend to checking for fake or cloned plates. Plate recognition technology is also applicable in various scenarios such as road tolls, parking management, weighing systems, traffic guidance, road inspections, vehicle dispatching, and vehicle inspections. With its wide application, how can plate recognition technology better serve these diverse applications and special cases? Faced with new challenges, we start with the plate recognition system.
Operation Principle:
License plate recognition involves the dynamic video or static image of a license plate, with automatic recognition of the license plate color and other pattern recognition technologies. The core of this technology includes license plate location algorithms, character segmentation algorithms, and a comprehensive optical character recognition system that should encompass vehicle detection, image capture, license plate recognition, and several other components. When the vehicle detection section detects the arrival of a vehicle, it triggers the image capture unit to collect the current visual frequency image. The license plate recognition unit processes the image, locates the license plate, then segments the characters for recognition and outputs the license plate number. Due to the 24/7 road traffic, license plate recognition ensures the accuracy of night-time identification by supplementing light with LED strobe lights or flashlights. The diagram below illustrates the composition structure of a typical license plate recognition system, where the front-end equipment connects to the back-end platform through a transmission network. The recognition output of a license plate recognition system is usually completed through the following steps: Vehicle Detection: Technologies such as buried loop detection, infrared radar detection, and video detection can be used. The process of sensing vehicles triggers image capture and capture. Image Capture: High-definition cameras capture the host in real-time, continuously recording and collecting passing vehicles. Preprocessing: Includes noise filtering, automatic white balance, automatic exposure, gamma correction, edge enhancement, contrast adjustment, etc. License Plate Location: Scans the grayscale image after preprocessing to determine the license plate area. Character Segmentation: After locating the license plate area in the image, processes it through grayscale and binarization to accurately locate character regions based on the size characteristics. Character Recognition: Scales and segments the divided characters, extracts features, and matches them with standard character expressions from the character database template. Result Output: Outputs the license plate recognition result in text format.
