Document Verification System

This document presents a comprehensive proof-of-concept prototype for an advanced document verification system. The system demonstrates sophisticated forensic detection capabilities for analyzing identity documents including passports, driver's licenses, and permanent resident cards (green cards).

Core Proposition

The fundamental insight driving this system is that document fraud can be detected and prevented through two complementary approaches:

• Local Forensic Analysis: Detecting tampering, forgery, and manipulation through image forensics, pattern recognition, and consistency checking
• Cross-Database Verification: Validating extracted document data against authoritative government databases to confirm identity and detect mismatches

System Capabilities

The prototype implements the first component (local forensic analysis) with over 80 detection methods across seven specialized modules. This demonstrates the technical feasibility and establishes the foundation for future database integration.

Key Differentiators

Analysis Pipeline

Every document uploaded to the system passes through a comprehensive analysis pipeline:

Technology Stack

The passport analysis module implements comprehensive verification aligned with international standards for machine-readable travel documents.

MRZ (Machine Readable Zone) Processing

Full implementation of ICAO Document 9303 specifications:

• TD1 Format: 3 lines x 30 characters (ID cards)
• TD2 Format: 2 lines x 36 characters (visas)
• TD3 Format: 2 lines x 44 characters (passports)
• Checksum Validation: 7-3-1 weighted algorithm for field integrity

Detection Heuristics

Extracted Data Fields

The system extracts and validates the following fields from passport MRZ:

Comprehensive detection system supporting all 50 US states plus the District of Columbia, with state-specific license number pattern recognition.

State Coverage

The system recognizes license number formats for all jurisdictions:

• Numeric Formats: California (8 digits), Texas (8 digits), Florida (13 digits)
• Alphanumeric Formats: New York (9 chars), Illinois (12 chars), Pennsylvania (8 chars)
• Letter-Prefix Formats: Ohio (2 letters + 6 digits), Virginia (letter + 8-11 digits)

Detection Signals (15 Weighted)

PDF417 Barcode Analysis

The system detects and analyzes AAMVA-compliant PDF417 barcodes containing encoded license data, providing a secondary validation source for extracted information.

Specialized module for Permanent Resident Card (Form I-551) analysis with 18 weighted anti-fraud detection signals.

USCIS Format Validation

• A-Number Format: Validates A-XXXXXXXX or A-XXXXXXXXX format (8-9 digits)
• Card Number Format: Validates XXX0000000000 format with prefix extraction
• Category Codes: Recognizes 100+ immigration categories (IR, EB, DV, F, etc.)

Detection Signals (18 Weighted)

USCIS Online Verification Link

The system provides direct links to USCIS Case Status Online for manual verification of immigration status using receipt numbers.

The forensic analysis suite comprises seven specialized modules, each targeting specific manipulation techniques and providing independent risk assessments.

Module Overview

Risk Scoring System

Each module produces an independent risk score, which are combined using weighted averaging:

Verdict Levels

MINIMAL (0-15%) LOW (15-35%) MODERATE (35-55%) HIGH (55%+)

The document tampering detection module is the primary anti-fraud component, implementing region-aware forensic analysis specifically designed to detect edited and manipulated documents.

Semantic Region Detection

The system first identifies critical document regions before applying forensic analysis:

• Face Region: Biometric photo area - highest manipulation target
• MRZ Region: Machine-readable zone - critical data area
• Text Blocks: Name, dates, and other personal information
• Signature Block: Signature area for tampering detection

Detection Methods

High-Importance Region Weighting

Anomalies detected in critical regions (face, MRZ) receive higher weight in the final risk calculation, as these areas are most commonly targeted in document fraud.

The core proposition extends beyond local document analysis. By integrating with authoritative government databases, we can create a comprehensive verification pipeline that cross-references document data across multiple sources.

System Architecture Diagram

Value Proposition

Cross-database verification enables detection of fraud scenarios that local analysis cannot identify:

• Valid-looking documents with fabricated data not matching any records
• Stolen identities where document data exists but belongs to another person
• Expired or revoked documents that appear visually valid
• Inconsistencies between passport, license, and immigration records

To transition from prototype to production deployment, the following requirements must be addressed across technical, security, legal, and operational domains.

Technical Requirements

Security & Compliance Requirements

Legal & Partnership Requirements

• Memoranda of Understanding (MOUs) with each data-sharing agency
• Data Use Agreements specifying permitted uses and retention policies
• Operator Background Checks and security clearances as required
• Legal Framework for acting on verification results

This prototype demonstrates the technical feasibility of advanced document verification through computer vision and forensic analysis. The system provides a solid foundation for a comprehensive identity document verification solution.

What This Prototype Demonstrates

• Sophisticated forensic analysis with 80+ detection methods across 7 modules
• Multi-document support for passports, driver's licenses, and green cards
• Standards-compliant MRZ decoding and barcode parsing
• Professional operator interface designed for document review workflows
• Region-aware tampering detection focusing on high-value document areas

Recommended Next Steps