TY - GEN
T1 - Recognition of broken characters from historical printed books using Dynamic Bayesian Networks
AU - Likforman-Sulem, Laurence
AU - Sigelle, Marc
PY - 2007/12/1
Y1 - 2007/12/1
N2 - This paper investigates the application of dynamic Bayesian networks (DBNs) to the recognition of degraded characters from historical printed books. This framework allows us to capture the 2D nature of character images by the coupling of two HMMs (Hidden Markov Models). The vertical HMM observes image columns while the horizontal HMM observes image rows respectively. Two coupled DBN architectures are proposed to model interactions between these two streams. We present experiments on real degraded characters extracted from an ancient printed book (17th century). These experiments demonstrate that coupled architectures significantly better cope with broken characters than non coupled ones and than discriminative methods such as SVMs.
AB - This paper investigates the application of dynamic Bayesian networks (DBNs) to the recognition of degraded characters from historical printed books. This framework allows us to capture the 2D nature of character images by the coupling of two HMMs (Hidden Markov Models). The vertical HMM observes image columns while the horizontal HMM observes image rows respectively. Two coupled DBN architectures are proposed to model interactions between these two streams. We present experiments on real degraded characters extracted from an ancient printed book (17th century). These experiments demonstrate that coupled architectures significantly better cope with broken characters than non coupled ones and than discriminative methods such as SVMs.
U2 - 10.1109/ICDAR.2007.4378698
DO - 10.1109/ICDAR.2007.4378698
M3 - Conference contribution
AN - SCOPUS:51149090156
SN - 0769528228
SN - 9780769528229
T3 - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
SP - 173
EP - 177
BT - Proceedings - 9th International Conference on Document Analysis and Recognition, ICDAR 2007
T2 - 9th International Conference on Document Analysis and Recognition, ICDAR 2007
Y2 - 23 September 2007 through 26 September 2007
ER -