This paper presents an Italic/Roman word type recognition system without a priori knowledge on the characters’ font. This method aims at analyzing old documents in which character segmentation is not trivial. Therefore our approach segments the document into words and analyse the text word per word. To define the word style, we combine three criteria which are based on the visual differences between a word and a slanted version of the same word. These criteria are defined thanks to features computed from the vertical projection profile of the word. Because we do not assume a specific slant angle, we compute these measures on a whole range of possible slant angles and then sum the obtained scores. Our results show a ratio of 100 % recognition for Italic words and 97.2 % for Roman words.