This paper presents a new approach for Handwritten Word Recognition based on Hidden Markov Model theory and the sliding window 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 window step are considered: Regular Step and Progressive Step. Experimental results showing the improvements obtained for basic word lexicon recognition are reported in the paper.
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