TY - GEN
T1 - Multi-experts for touching digit string recognition
AU - Wang, Xian
AU - Govindaraju, Venu
AU - Srihari, Sargur
N1 - Publisher Copyright:
© 1999 IEEE.
PY - 1999
Y1 - 1999
N2 - 84.6% of touching digit strings have only two digits touching, 12.3% have three digits touching and 3.1% have more than three digits touching. We present a multi-expert approach to recognize touching digit pairs (TDP) and touching digit triples (TDT). We combine holistic and traditional segmentation methods. 25,686 TDP training samples and 2,778 TDP testing samples collected from USPS mail are used in our experiment. The holistic method outperforms the traditional segmentation-based methods. The multi-expert combination has the best performance: a correct recognition rate of 91.1% on TDP.
AB - 84.6% of touching digit strings have only two digits touching, 12.3% have three digits touching and 3.1% have more than three digits touching. We present a multi-expert approach to recognize touching digit pairs (TDP) and touching digit triples (TDT). We combine holistic and traditional segmentation methods. 25,686 TDP training samples and 2,778 TDP testing samples collected from USPS mail are used in our experiment. The holistic method outperforms the traditional segmentation-based methods. The multi-expert combination has the best performance: a correct recognition rate of 91.1% on TDP.
UR - https://www.scopus.com/pages/publications/2042437212
U2 - 10.1109/ICDAR.1999.791909
DO - 10.1109/ICDAR.1999.791909
M3 - Conference contribution
AN - SCOPUS:2042437212
T3 - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
SP - 804
EP - 807
BT - Proceedings of the 5th International Conference on Document Analysis and Recognition, ICDAR 1999
PB - IEEE Computer Society
T2 - 5th International Conference on Document Analysis and Recognition, ICDAR 1999
Y2 - 20 September 1999 through 22 September 1999
ER -