Arabic handwritten word recognition with large vocabulary based on explicit segmentation

In this paper, an Arabic handwritten word recognition system for wide vocabulary using the analytical approach is presented. After the segmentation phase, the characters are recognized using assumption generation of letters. Thus, the proposed system generates assumptions of words by concatenation of letters assumption. Thereafter, a filtering of these words assumption is achieved thanks to a language dictionary. The system showed good performances when applied on a 500 word images dataset.