Document Authenticity Verification via Vector Encoding
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Solution Overview
Problem
The manual review of millions of travel documents for authenticity is slow, inefficient, not scalable, and expensive, leading to inconvenient delays for travelers.
Innovation Solution
A method using an electronic device to receive an image of a document, assign a label based on the document's text, and encode it into a low dimensionality vector for comparison against a database, determining authenticity based on calculated distances and thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review of documents is performed, then authenticity can be determined with high accuracy, but the process becomes slow and inefficient
Solution Approach 1:
The patent introduces an intermediary system consisting of image encoding, vector representation, and similarity calculation mechanisms that bridge manual review accuracy with automated processing speed. The system encodes document images into vectors and calculates similarity metrics against authentic document templates, serving as a mediator that provides both speed and accuracy without requiring full manual review of each document.
2Reliability
If manual review of each document is performed, then fraudulent documents can be detected, but the cost and time consumption increase significantly
Solution Approach 1:
The patent applies partial action by performing automated similarity comparison on all documents and reserving manual review only for cases where the automated system detects potential fraud or low confidence matches. This selective approach maintains high fraud detection capability while significantly reducing the time loss associated with reviewing every single document manually.
3Quantity of substance
If the volume of document reviews increases to handle millions of travelers, then travel demand can be met, but manual review becomes non-scalable and expensive
Solution Approach 1:
The patent replaces the mechanical manual review system with an automated computational system that uses image encoding, vector mathematics, and similarity algorithms. This substitution enables the system to handle millions of documents efficiently, as the automated system can process documents in parallel without the complexity and cost constraints of scaling human reviewers.
4Productivity
If automated image processing is used, then processing speed increases, but the ability to detect subtle fraudulent modifications decreases
Solution Approach 1:
The patent performs preliminary automated filtering and similarity comparison to quickly identify obviously authentic or fraudulent documents. For documents that pass the initial automated screening or show ambiguous results, the system prepares them for more detailed examination, ensuring that subtle fraudulent modifications are not missed while maintaining high overall processing speed.
Data Source
AI summary
A method for determining authenticity of a document is provided that includes receiving, by an electronic device, an image of a document, assigning a label to the image, and obtaining vectors for each image in a subset of images. Each image is of a document and is assigned the same label as the received image. Moreover, the method includes encoding the received image into a vector, calculating a distance between the vector of the received image and each obtained vector, comparing each of the calculated distances against a threshold distance, and calculating a number of the calculated distances that are less than or equal to the threshold distance. In response to determining the calculated number is at least equal to a required number, the document in the received image is determined to be authentic. Otherwise, the received image requires manual review.