  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.
