2018/10/09 by Xusen Yin, Nada Aldarrab, Yin, Xusen +5
Computer Science · #Computation and Language (cs.CL) #Digital Media Forensic Detection #FOS: Computer and information sciences #Handwritten Text Recognition Techniques #Image Processing and 3D Reconstruction #cs.CL
paper · pdf · doi:10.48550/arxiv.1810.04297
International Conference on Document Analysis and Recognition 2019 Long paper
openalex publication_date 2018/10/09 · arxiv created 2019/06/02 · arxiv updated 2019/06/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
European libraries and archives are filled with enciphered manuscripts from the early modern period. These include military and diplomatic correspondence, records of secret societies, private letters, and so on. Although they are enciphered with classical cryptographic algorithms, their contents are unavailable to working historians. We therefore attack the problem of automatically converting cipher manuscript images into plaintext. We develop unsupervised models for character segmentation, character-image clustering, and decipherment of cluster sequences. We experiment with both pipelined and joint models, and we give empirical results for multiple ciphers.