VIN Verification via Windshield Photography and Image Processing
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Solution Overview
Problem
Current methods for auditing vehicle identification numbers (VINs) face challenges such as unclear photographs due to windshield reflections, fraud from reused images, and dishonest recording practices, leading to inefficiencies in verifying vehicle sales and inventory.
Innovation Solution
A system utilizing crowdsourcing techniques, including CAPTCHAs and crowd voting, to verify digital photographs of VINs, which detects fraud and ensures accurate identification through consensus verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If auditors take photographs of VINs through windshield glass, then VIN identification can be performed, but photograph quality deteriorates due to reflections and visual artifacts
Solution Approach 1:
The patent introduces an intermediary processing system that receives photographs taken through windshield glass and applies image processing techniques to remove reflections and visual artifacts. This intermediary step between photograph capture and VIN reading resolves the contradiction by maintaining ease of operation while improving photograph quality through computational mediation.
Solution Approach 2:
The patent replaces the mechanical/optical limitation of clear glass access with an electronic/image processing solution. Instead of requiring physical access to clean VIN plates, the system uses digital image processing to substitute for the lost optical clarity, thereby maintaining operational ease while improving readability.
2Productivity
If auditors use single photographs for repeated verification, then verification process is efficient, but fraud risk increases due to image reuse
Solution Approach 1:
The patent implements periodic re-photographing requirements where VIN photographs must be taken at different time intervals and from different angles. This periodic action prevents fraud by ensuring that single reused photographs cannot satisfy multiple verification requirements, while still maintaining efficiency through automated processing of multiple images.
Solution Approach 2:
The system performs preliminary validation checks on photographs before they are accepted for verification, including checks for authenticity, timing, and angle variety. This preliminary action prevents fraudulent reuse of images by establishing validation criteria upfront, thereby maintaining both efficiency and reliability.
3Ease of manufacture
If auditors manually record VINs on clipboards, then recording is simple, but dishonest recording practices occur leading to verification failures
Solution Approach 1:
The patent replaces manual clipboard recording with electronic photograph-based verification systems. The mechanical act of writing VINs is substituted with automated image capture and digital processing, eliminating the opportunity for dishonest manual recording while maintaining simplicity through user-friendly photograph-taking interfaces.
Solution Approach 2:
The system creates accurate digital copies of VIN plates through photographing, replacing manual transcription with automated optical character recognition. This copying process eliminates recording errors and dishonest practices by directly capturing the actual VIN from the vehicle rather than relying on human transcription.
4Measurement precision
If auditors access locked vehicles to check VIN plates, then accurate VIN reading is possible, but vehicle access becomes difficult due to locked doors
Solution Approach 1:
The patent inverts the traditional approach by not requiring access to the locked vehicle interior. Instead of opening doors to reach VIN plates in doorjambs, the system photographs VINs visible through windshields from the exterior, thereby solving the access difficulty while maintaining reading accuracy through image processing.
Data Source
AI summary
A method and system for auditing and verifying vehicle identification numbers (VINs) with crowdsourcing. Digital photographs of vehicle VINs are collected and verified with independent crowdsourcing techniques including crowd voting techniques used in CAPTCHAs, etc. The crowdsourcing techniques are also used to detect fraud associated with VIN audits of vehicle lots.