Automated ICAO/ISO Compliance Validator for ID Portraits

AbstractThe manual verification of identity document portraits against internationalstandards remains a labor-intensive and error-prone process, limiting scalability inhigh-volume digital identity workflows. This paper presents an automated, open-sourcecompliance validator that programmatically enforces ICAO Doc 9303 and ISO/IEC19794-5 requirements for ID portrait photographs. The proposed system integratesMediaPipe's modern Tasks API for robust face landmark extraction, geometric rulebased checks for head-to-frame ratio (70–80%), eye-line positioning (50–60% fromtop), and head pose tolerance (±10°), alongside environmental assessments forbackground uniformity and lighting consistency. A modular, thread-safe architectureenables dual deployment: a stateless Flask REST API for system integration and across-platform Tkinter graphical interface for interactive validation, both producingstructured JSON reports with per-check status, quantitative metrics, and actionablerecommendations. Evaluation on a curated dataset of 500 portrait images across threedifficulty tiers demonstrates high precision (0.95) and recall (0.93) for overallcompliance detection, with average end-to-end latency of 218 ± 24 ms on CPUhardware. The validator reduces manual review overhead by >85% while maintainingfull auditability through ephemeral, privacy-preserving processing. By bridgingstandards-aligned rule enforcement with production-ready deployment, this workprovides a reproducible, offline-capable foundation for scalable identity photographyworkflows in resource-constrained environments.