Appearance Based Models in Document Script Identification

In this paper we employ appearance based models for document script identification. They are employed to identify scripts at both paragraph and word level. Elaborate experimentation has been conducted which has revealed that they are robust enough to handle highly confusing scripts and their performance does not degrade drastically even in the presence of noise. A generic script identification has been attempted, to identify both Asian and European scripts by considering a dataset of twenty different languages.