HMM Based Handwritten Word Recognition System by Using Singularities

This paper presents a new approach for handwritten word recognition based on hidden Markov model theory and the sliding windows technique. The new approach uses specific singularity markers to support the recognition phase: the static marker and the dynamic marker. Moreover, different strategies for sliding windows step are considered: regular step and progressive step. Experimental results showing the improvements obtained for basic word lexicon recognition are reported in the paper.