Codebook for Writer Characterization: A Vocabulary of Patterns or a Mere Representation Space?

Codebook-based representations have been effectively employed for writer identification. Most of the codebook-based methods generate a codebook by clustering a set of patterns extracted from an independent data set. The probability of occurrence of the codebook patterns in a given writing is then used to characterize its author. This study investigates the hypothesis that the codebook is merely a representation space and the codebook patterns themselves do not affect the writer identification performance. The idea is validated by first using codebooks in different scripts from those of writings in question and then by using a synthetically generated codebook. A number of data sets with handwritten samples in Arabic, French, English, German, Urdu and Greek are considered in our series of evaluations. Experiments conducted with different codebooks report interesting results which validate the ideas put forward in this study.