The Snippet Statistics of Font Recognition
Jakub Lidke, Christian Thurau, Christian Bauckhage · 2010
This paper considers the topic of automatic font recognition. The task is to recognize a specific font from a text snippet. Unlike previous contributions, we evaluate, how the frequencies of certain letters or words influence automatic recognition systems. The evaluation provides estimates on the general feasibility of font recognition under various changing conditions. Results on a data-set containing 747 different fonts shows that precision can vary between 16% and 94%, dependent on (i) which letters are provided, (ii) how many letters are provided, and (iii) which language is used - as these factors considerably influence the text snippet statistics. As a second contribution, we introduce a novel bag-of-features based approach to font recognition.