Text-Independent Writer Identification and Verification on Offline Arabic Handwriting

In this paper, we evaluate the performance on Arabic handwriting of the text-independent writer identification methods that we developed and tested on Western script in recent years. We use the IFN/ENIT data in the experiments reported here and our tests involve 350 writers. The results show that our methods are very effective and the conclusions drawn in previous studies remain valid also on Arabic script. High performance is achieved by combining textural features (joint directional probability distributions) with allographic features (grapheme-emission distributions).

• Type: Conference
• Year: 2007
• Where: ICDAR
• Authors: Marius Bulacu, Lambert Schomaker, Axel Brink
• Keywords: Arabic Handwriting, Directional Probability Distributions, Document Analysis, ICDAR 2007, Writer Identification Methods