Off-Line Multi-Script Writer Identification Using AR Coefficients

The problem of writer identification in a multiscript environment is attempted using a twodimensional (2D) autoregressive (AR) modelling technique. Each writer is represented by a set of 2D AR model coefficients. A method to estimate AR model coefficients is proposed. This method is applied to an image of text written by a specific writer so that AR coefficients are obtained to characterize the writer. For a given sample, AR coefficients are computed and its L2 distance with each of the stored (writer) prototypes identifies the writer for the sample. The method has been tested on datasets of two different scripts, namely RIMES containing 382 French writers and ISI consisting of samples from 40 Bengali writers. Modelling of writing styles using different context patterns at different image resolution has been investigated. Experimental results show that the technique achieves results comparable with that of the previous approaches.

• Type: Journal
• Year: 2009
• Where: ICDAR
• Authors: Utpal Garain, Thierry Paquet
• Keywords: AR Model Coefficients, Document Analysis, ICDAR 2009, Specific Writer, Writer Identification