Joint Transcription and Decryption of Images of Encrypted Handwritten Documents: A Comparison with the Traditional Pipeline
For researchers working on historical encrypted manuscripts, this work introduces a novel end-to-end method that could reduce error propagation, but the results are preliminary and lack quantitative comparison.
The paper proposes an end-to-end approach for directly decrypting images of encrypted handwritten documents, bypassing the traditional two-stage transcription-then-decryption pipeline. Using the Copiale cipher, the joint model shows promise as an alternative, though no concrete performance numbers are provided.
Historical encrypted manuscripts present a challenging problem at the intersection of cryptology, linguistics, paleography, and computer vision. Current automatic decipherment approaches usually rely on a two-stage pipeline: transcription of cipher symbols from manuscript images, followed by decryption into plaintext. However, this design is sensitive to transcription errors, which propagate to the final output. We present Direct Image Decryption, an end-to-end approach that directly maps encrypted manuscript images to plaintext, bypassing the intermediate transcription stage. Using the Copiale cipher as a case study, we build a synthetic data generation pipeline to create large-scale cipher-like training data and compare the traditional pipeline with the proposed joint architecture. Results show that joint image-to-plaintext modeling is a promising alternative to traditional transcription-based pipelines.