Decipherment of Historical Manuscript Images
| Autor: | Kevin Knight, Beáta Megyesi, Xusen Yin, Nada Aldarrab |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
FOS: Computer and information sciences
Information retrieval Computer Science - Computation and Language Character (computing) Computer science business.industry 05 social sciences Plaintext Cryptography 02 engineering and technology 050105 experimental psychology Cipher 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 0501 psychology and cognitive sciences Decipherment business Computation and Language (cs.CL) |
| Zdroj: | ICDAR |
| Popis: | 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. International Conference on Document Analysis and Recognition 2019 Long paper |
| Databáze: | OpenAIRE |
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