License Plate Detection via Image Segmentation and Perspective Correction
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Solution Overview
Problem
Current systems face challenges in accurately detecting and reading license plate information from images captured by mobile devices due to varying angles, distances, and the presence of other objects, making it difficult to scale license plate image capture processes used by law enforcement to mobile apparatuses.
Innovation Solution
A computer-implemented method and system that uses an image sensor to capture and transmit optical images, with a remote server automatically identifying vehicle information by comparing the image with a unique feature database, enabling the extraction of license plate information and vehicle configuration details.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If stationary traffic cameras are used to photograph license plates at specific locations and angles, then accurate license plate image collection is achieved, but the system cannot adapt to different angles, distances, or mobile apparatuses
Solution Approach 1:
The patent applies dynamics by transitioning from static camera systems to mobile apparatuses with adjustable positioning. The system enables dynamic capture of license plates from varying angles and distances while maintaining identification accuracy through image processing algorithms that compensate for perspective transformations and distortion.
Solution Approach 2:
The system changes parameters such as camera angle, distance, and positioning flexibility to adapt to different capture scenarios. By allowing these parameters to vary rather than being fixed, the system maintains license plate detection accuracy across diverse conditions while enhancing versatility.
2Measurement precision
If manual camera installation and configuration is performed for specific angles and locations, then accurate license plate photography is achieved, but the system becomes complex and difficult to scale
Solution Approach 1:
The patent implements self-service by enabling mobile apparatuses to autonomously capture and process license plate images without requiring manual camera installation or configuration. The system automatically detects and identifies license plates through image processing algorithms, eliminating the need for complex manual setup while maintaining accuracy.
Solution Approach 2:
The system replaces mechanical camera installation and configuration processes with automated image processing techniques. Instead of physically configuring cameras for specific angles and locations, the system uses computational methods to correct perspective, lighting, and positioning variations, thereby reducing mechanical complexity.
3Adaptability or versatility
If mobile apparatuses are used to capture images at various angles and distances, then system versatility is improved, but license plate information detection accuracy deteriorates
Solution Approach 1:
The patent applies feedback by implementing iterative image processing that analyzes captured images and adjusts processing parameters based on detected characteristics. The system continuously refines its detection algorithms based on the specific imaging conditions, maintaining high accuracy across varying angles and distances through adaptive feedback loops.
Solution Approach 2:
The system performs preliminary image processing actions such as perspective transformation correction, distortion compensation, and enhancement algorithms before license plate detection. These preliminary actions prepare the image data to maintain high detection accuracy even when captured from diverse angles and distances by mobile apparatuses.
4Adaptability or versatility
If multiple object images are present in the captured image, then real-world complexity is reflected, but license plate identification becomes more difficult
Solution Approach 1:
The patent applies segmentation by dividing the captured image into multiple regions of interest and processing each region separately. The system identifies and isolates potential license plate locations from other objects in the scene, allowing focused analysis on candidate areas while filtering out irrelevant information from multiple objects present in the image.
Solution Approach 2:
The system extracts and isolates the license plate region from the broader image context, separating the target object from surrounding elements. By extracting the license plate area and processing it independently, the system maintains identification accuracy even when multiple objects are present in the original captured image.
Data Source
AI summary
A system and method is provided for automatically identifying a vehicle and facilitating a transaction related to the vehicle. The system includes a first computing apparatus having an image sensor that captures optical images of a vehicle and an interface that transmits the captured optical image. The system further includes a remote server that receives the transmitted and captured optical image, automatically scans the captured optical image to identify one or more distinguishing features of the vehicle, automatically compares the identified distinguishing features with a unique feature database that includes respective vehicle identification information associated with unique vehicle features, automatically identify the vehicle identification information that corresponds to the vehicle upon determining a match, automatically identify vehicle configuration information based on the identified vehicle identification information, and automatically transmit the identified vehicle configuration information to the first computing apparatus to be displayed thereon.