AI Document Classification via Shape, Barcode, and OCR Verification
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Solution Overview
Problem
Manual verification of document information from uploaded images is time-consuming and prone to errors, as existing automatic document reading systems are difficult to create and unreliable, leading to long turnaround times and increased costs due to the need for human labor.
Innovation Solution
An AI system capable of classifying and verifying documents by conducting optical character recognition (OCR), identifying visual features, and decoding barcodes to extract and validate document information, using machine learning to match document shapes and types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual verification of document information is used, then accuracy can be maintained through human judgment, but processing time increases significantly and costs rise due to human labor requirements
Solution Approach 1:
The patent replaces manual mechanical verification processes with an automated AI-based document reading system that uses optical character recognition (OCR), machine learning models, and barcode decoding to extract and verify document information automatically, eliminating the need for human operators while maintaining high accuracy through multiple verification mechanisms including shape matching, text validation, and barcode cross-checking
Solution Approach 2:
The system enables documents to be self-verified through automated extraction of information from multiple sources (text content, barcodes, document shape) and cross-validation of these features against expected patterns, allowing the verification process to occur without human intervention and significantly reducing processing time while maintaining reliability through algorithmic validation
2Productivity
If automated document reading systems are implemented, then processing speed increases, but system complexity increases and reliability decreases due to difficulty in creating accurate automatic reading systems
Solution Approach 1:
The patent divides the document verification process into distinct modular components: optical character recognition for text extraction, barcode decoding for machine-readable data extraction, shape detection for document type identification, and machine learning-based classification. Each module handles a specific aspect of verification, making the overall system more manageable and easier to optimize individually while maintaining high processing speed through parallel operation of these segments
Solution Approach 2:
The system employs a universal AI-based document reading platform that can handle multiple document types (driver's licenses, passports, identification cards) and multiple information sources (text, barcodes, shapes) through a single integrated system. This multi-functional approach reduces overall system complexity compared to having separate specialized systems for each document type, while maintaining high processing speed through optimized universal algorithms
3Reliability
If multiple document features are analyzed for verification, then accuracy improves, but processing time increases due to the complexity of analyzing text, barcodes, and visual features simultaneously
Solution Approach 1:
The system performs preliminary analysis of document features in a optimized sequence, starting with quick shape detection to identify document type, followed by barcode decoding if present, then text extraction via OCR. By performing actions in this predetermined optimal sequence and using results from earlier steps to guide subsequent analysis, the system achieves high verification accuracy through multiple feature analysis while minimizing total processing time through intelligent task scheduling and early termination when sufficient verification is achieved
Data Source
AI summary
Artificial intelligence (AI) systems of the inventive subject matter are directed to receiving uploaded images containing one or more document, identifying the type of documents received, and returning information contained in those documents. Upon receiving an image containing a document, the AI system: checks for barcodes, OCRs any text, detects visual features, and detects an overall document shape. The AI system can then use any information gathered during those steps to ultimately verify information contained in the document.