FontCode: Embedding Information in Text Documents using Glyph Perturbation
This provides a method for embedding metadata, barcodes, cryptographic messages, or signatures in text documents, potentially useful for document security and management, though it appears incremental as it builds on existing generative models.
The authors tackled the problem of embedding information in text documents by introducing FontCode, which perturbs glyphs of characters to encode messages while preserving text content, achieving recognition from vector graphics, pixel images, or printed paper with a new error-correction scheme.
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.