Fusion of Explicit Segmentation Based System and Segmentation-Free Based System for On-Line Arabic Handwritten Word Recognition

The complexity and viariability of the Arabic handwriting makes difficult the implementation of an efficient recognition system through the use of a unique recognition engine. In this paper, two handwriting word recognition systems are combined in order to take advantage of their complementarities. The first one is a segmentation free based system that uses the generative classifier HMM. The second system is discriminative based. Relying on analytical approach, it proceeds with explicit segmentation of words into graphemes. Different combination strategies are compared including sum, product, Borda count and Dempster-Shafer rules. The experimental results conducted on ADAB database demonstrate a significant improvement of recognition accuracy of 5% compared to the segmentation free based system and 9% compared to the analytical based system.