FontCode: Embedding Information in Text Documents using Glyph Perturbation

TL;DR

FontCode is a novel technique that embeds information into text documents by subtly perturbing glyphs, enabling covert data encoding and retrieval while maintaining the document's visual integrity.

Contribution

The paper introduces a new glyph perturbation method for embedding and recovering information in text documents, including an error-correction scheme and multiple practical applications.

Findings

Successfully embeds data with minimal visual disturbance.

Achieves reliable information recovery from various formats.

Demonstrates diverse applications like metadata and cryptography.

Abstract

We introduce FontCode, an information embedding technique for text documents. Provided a text document with specific fonts, our method embeds user-specified information in the text by perturbing the glyphs of text characters while preserving the text content. We devise an algorithm to chooses unobtrusive yet machine-recognizable glyph perturbations, leveraging a recently developed generative model that alters the glyphs of each character continuously on a font manifold. We then introduce an algorithm that embeds a user-provided message in the text document and produces an encoded document whose appearance is minimally perturbed from the original document. We also present a glyph recognition method that recovers the embedded information from an encoded document stored as a vector graphic or pixel image, or even on a printed paper. In addition, we introduce a new error-correction coding scheme that rectifies a certain number of recognition errors. Lastly, we demonstrate that our technique enables a wide array of applications, using it as a text document metadata holder, an unobtrusive optical barcode, a cryptographic message embedding scheme, and a text document signature.