Baseline estimation for Arabic handwritten words

Baseline information has been used for diverse purposes in handwriting research. The baseline represents a first orientation in a word and it is often a precondition for subsequent algorithms, including preprocessing tasks, segmentation and feature extraction for recognition systems. Approaches based on the horizontal projection histogram are used for Arabic printed text but they are ill-suited for Arabic handwritten words. In this paper we present a method that is completely based on polygonally approximated skeleton processing. The central algorithm is concerned with finding features in the skeleton and processing linear regression analysis. Our method performs very well as long as the model assumption of one straight line applies. We tested the method on 26459 isolated Tunisian town names written by 411 writers (IFN/ENIT-database).