Detecting whether a document — an ID card, a certificate — has been digitally altered is a genuinely hard vision problem, and it's worth being honest about what's checkable today versus what requires more sophisticated forensics than a straightforward pipeline provides.
What's checkable with a reasonable pipeline
- Font and layout consistency against a known template for that document type — misaligned text or an inconsistent font is a common tell.
- Compression artifacts around a suspected edit region, which basic error-level analysis can sometimes surface.
- Metadata inconsistencies (creation date, editing software) when the original file, not just a photo of it, is available.
What's genuinely hard
A well-executed edit on a photographed (not digital) document, using competent editing tools, can defeat most straightforward checks. Be honest with users and stakeholders about this limitation rather than implying a pipeline catches all tampering.
See document AI for invoices: an extraction schema.
GenAI engineer and AI product builder with 2+ years shipping production-grade AI systems: RAG pipelines, fine-tuned LLMs, hybrid retrieval and multi-modal apps across vision, speech and OCR, architected end to end from ingestion to deployment. Leads engineering for SCULT INDIA's 14-member team, founded the 500+ member TechVerse Enclave community and has mentored 200+ students. Three hackathon first prizes: Changethon 2025 (IIT Roorkee), Product Genesis at Vividhotsava 2025 (CSJMU Kanpur) and BYTEBATTLE (MeetKats).
Open to GenAI roles, hackathon judging, mentorship sessions and guest talks at colleges. Email pranjulrathour41@gmail.com.
