This paper is focused on the optimization of the computational efficiency of a multi-stream word recognition system. The aim of this work is to optimize the multi-stream decoding step in order to reduce the recognition time and the complexity to allow combining a large number of streams. Two different multi-stream decoding strategies are compared based on two-level and HMM-recombination algorithms. Experiments carried out on public handwritten word databases show significant speed gains at decoding while keeping the same performances, in addition to new insights for combining a large number of streams.
['Yousri Kessentini', 'Thierry Paquet', 'Ahmed Guermazi']
An Optimized Multi-stream Decoding Algorithm for Handwritten Word Recognition