Classification of Phonetic Characters by Space-Filling Curves

Ancient printed documents are an infinite source of knowledge, but digital uses are usually complicated due to the age and the quality of the print. The Linguistic Atlas of France (ALF) maps are composed of printed phonetic words used to locate how words were pronounced over the country. Those words were printed using the Rousselot-Gillieron alphabet (extension of Latin alphabet) which bring character recognition problems due to the large number of diacritics. In this paper, we propose a phonetic character recognition process based on a space-filling curves approach. We proposed an original method adapted to this particular data set, able to finely classify, with more than 70% of accuracy, noisy and specific characters.