DocumentCode
1990412
Title
Arabic character recognition using particle swarm optimization with selected and weighted moment invariants
Author
Sarfraz, Muhammad ; Al-Awami, Ali Taleb Ali
Author_Institution
Dept. of Inf. & Comput. Sci., King Fahd Univ. of Pet. & Miner., Dhahran
fYear
2007
fDate
12-15 Feb. 2007
Firstpage
1
Lastpage
4
Abstract
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.
Keywords
character recognition; image segmentation; particle swarm optimisation; Arabic character recognition; Arabic text; particle swarm optimization; swarm-based optimization technique; weighted moment invariants; Character recognition; Computer science; Face detection; Feature extraction; Minerals; Object recognition; Particle swarm optimization; Petroleum; Shape; Speech recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on
Conference_Location
Sharjah
Print_ISBN
978-1-4244-0778-1
Electronic_ISBN
978-1-4244-1779-8
Type
conf
DOI
10.1109/ISSPA.2007.4555582
Filename
4555582
Link To Document