@article{(Open Science Index):https://publications.waset.org/pdf/12621,
	  title     = {Optimizing Feature Selection for Recognizing Handwritten Arabic Characters },
	  author    = {Mohammed Z. Khedher and  Gheith A. Abandah and  Ahmed M. Al-Khawaldeh},
	  country	= {},
	  institution	= {},
	  abstract     = {Recognition of characters greatly depends upon the features used. Several features of the handwritten Arabic characters are selected and discussed. An off-line recognition system based on the selected features was built. The system was trained and tested with realistic samples of handwritten Arabic characters. Evaluation of the importance and accuracy of the selected features is made. The recognition based on the selected features give average accuracies of 88% and 70% for the numbers and letters, respectively. Further improvements are achieved by using feature weights based on insights gained from the accuracies of individual features. },
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {1},
	  number    = {4},
	  year      = {2007},
	  pages     = {1038 - 1041},
	  ee        = {https://publications.waset.org/pdf/12621},
	  url   	= {https://publications.waset.org/vol/4},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 4, 2007},
	}