Title :
Network-based approach to online cursive script recognition
Author :
Sin, Bong-Kee ; Ha, Jin-Yong ; Oh, Se-Chang ; Kim, Jin H.
Author_Institution :
Multimedia Res. Labs., Korea Telecom, Seoul, South Korea
fDate :
4/1/1999 12:00:00 AM
Abstract :
The idea of combining the network of HMMs and the dynamic programming-based search is highly relevant to online handwriting recognition. The word model of HMM network can be systematically constructed by concatenating letter and ligature HMM´s while sharing common ones. Character recognition in such a network can be defined as the task of best aligning a given input sequence to the best path in the network. One distinguishing feature of the approach is that letter segmentation is obtained simultaneously with recognition but no extra computation is required
Keywords :
character recognition; handwriting recognition; hidden Markov models; HMMs; cursive script recognition; dynamic programming; letter segmentation; online handwriting recognition; word model; Character recognition; Computer science; Handwriting recognition; Hidden Markov models; Mathematical model; Neural networks; Pattern recognition; Probability; Silicon compounds; Viterbi algorithm;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/3477.752808
