TY - GEN
T1 - Arabic character recognition using particle swarm optimization with selected and weighted moment invariants
AU - Sarfraz, Muhammad
AU - Al-Awami, Ali Taleb Ali
PY - 2007
Y1 - 2007
N2 - A new Arabic character recognition system has been proposed using Moments as features. The proposed scheme works in such a way that the features are selected as well as weighted using a swarm-based optimization technique. For the sake of simplicity, it has been assumed that the Arabic text has already been preprocessed and segmented. Recognition results have been achieved up to 82% of accuracy. Authors believe that the 82% of accuracy is mainly due to not using very effective segmentation technique, otherwise the results could be above 95% as has been observed in the case of object recognition in an earlier paper of the authors.
AB - A new Arabic character recognition system has been proposed using Moments as features. The proposed scheme works in such a way that the features are selected as well as weighted using a swarm-based optimization technique. For the sake of simplicity, it has been assumed that the Arabic text has already been preprocessed and segmented. Recognition results have been achieved up to 82% of accuracy. Authors believe that the 82% of accuracy is mainly due to not using very effective segmentation technique, otherwise the results could be above 95% as has been observed in the case of object recognition in an earlier paper of the authors.
UR - https://www.scopus.com/pages/publications/51549103570
U2 - 10.1109/ISSPA.2007.4555582
DO - 10.1109/ISSPA.2007.4555582
M3 - Conference contribution
AN - SCOPUS:51549103570
SN - 1424407796
SN - 9781424407798
T3 - 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings
BT - 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings
ER -