Identity Document Barcode Verification Through Local Format Clustering
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Solution Overview
Problem
Existing barcode scanning technologies, particularly in mobile devices, face challenges in increasing scanning speed, accuracy, and managing processing power, especially when dealing with variations in barcode formats across different jurisdictions and versions of identity documents.
Innovation Solution
A system utilizing a camera in a mobile device to decode barcodes on identity documents by clustering barcode structures based on feature vectors, comparing format features, and optionally verifying with remote services to authenticate the documents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If barcode scanning is performed using a camera in a mobile device with image analysis, then portability and accessibility are improved, but scanning speed and accuracy deteriorate compared to specialized scanners
Solution Approach 1:
The patent segments the barcode verification process into multiple components: format feature extraction, clustering analysis, and validation checking. This segmentation allows the system to process barcodes more efficiently by focusing on structural characteristics rather than complete decoding, thereby improving scanning speed while maintaining portability
Solution Approach 2:
The system performs preliminary clustering of barcode formats during setup, creating reference profiles for different jurisdictions and versions. When scanning, it compares against pre-established clusters rather than analyzing from scratch, significantly reducing processing time while maintaining accuracy
2Measurement precision
If barcode verification relies on remote identification services, then verification accuracy is improved, but dependency on internet connectivity and external services increases
Solution Approach 1:
The patent introduces local clustering data as an intermediary between the barcode scanner and remote verification services. The system first performs local format matching using clustered reference data, and only engages remote services when local verification is inconclusive, reducing dependency while maintaining accuracy
Solution Approach 2:
The system implements self-service verification capabilities by maintaining local databases of barcode format clusters. It can independently verify barcodes against these local references without requiring constant external service intervention, thereby reducing dependency while preserving verification accuracy
3Adaptability or versatility
If the system clusters barcodes based on format features from multiple jurisdictions, then adaptability to different barcode formats is improved, but processing complexity increases
Solution Approach 1:
The patent transforms barcode verification from exact matching to parameter-based clustering. It extracts key format parameters (dimensions, patterns, structures) and groups barcodes into clusters based on these parameters, enabling flexible adaptation to different jurisdictions while simplifying processing through parameter abstraction
Data Source
AI summary
An identity document can be authenticated using format data of a barcode on the document, such as a barcode on a driver's license.