Vehicle Recognition via Real-Time Video Analysis and VIN Extraction
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Solution Overview
Problem
Modern mobile devices have advanced hardware capabilities but lack sophisticated software for real-time image processing and connecting visual data to financial information, limiting their ability to provide users with relevant information about vehicles in real-time.
Innovation Solution
The system uses real-time video analysis and object recognition to identify vehicles and match visual data with financial institution data, such as customer behavior history and transaction history, to provide users with detailed information about the vehicle, including pricing and budget impact, by capturing images of vehicle features like VIN numbers and presenting this information superimposed on the mobile device display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If real-time video analysis and object recognition are implemented to identify vehicles and provide financial information, then the usefulness and information completeness are improved, but the device complexity and processing requirements increase
Solution Approach 1:
The system segments the complex image processing task into distinct modules: image capture, vehicle detection, feature extraction (VIN, logos, emblems), and financial information retrieval. Each module handles a specific aspect of the overall process, reducing the complexity burden on any single component while maintaining comprehensive functionality.
Solution Approach 2:
The patent introduces an intermediary processing layer that bridges the gap between simple image capture and complex financial information delivery. This intermediary layer includes vehicle detection algorithms and feature extraction systems that translate raw images into structured data, which then connects to financial databases, effectively mediating between hardware capabilities and information requirements.
2Reliability
If sophisticated multi-tasking operating systems and high-resolution video cameras are utilized, then the capability and information quality are improved, but the energy consumption and processing load increase
Solution Approach 1:
The system implements partial action by selectively processing only relevant portions of captured images. Instead of analyzing entire high-resolution images in real-time, the system focuses on specific regions containing vehicle features (VIN numbers, logos, emblems), reducing processing load and energy consumption while maintaining reliable vehicle identification.
Solution Approach 2:
The patent employs periodic action through event-triggered processing where the system activates full image processing only when vehicle features are detected, rather than continuously processing all captured frames. This approach reduces energy consumption by keeping the processing system in a low-power state during non-critical periods while maintaining reliable detection capability when needed.
Data Source
AI summary
System, method, and computer program product are provided for using real-time video analysis to provide information about vehicles to a user. Through the user of real-time vision object recognition an image of a vehicle VIN number or a portion of a vehicle may be captured using an image capture device. The VIN number or the portion the vehicle that was captured via the real-time video analysis may be analyzed to determine information about the vehicle. The information may include information about the vehicle, such as the make, model, year, price, vehicle history, and the like. Furthermore, information about the individual's finances, such that an individual may know budgeting of purchasing a vehicle. The information about the vehicle and financial information about purchasing the vehicle is presented to the user.