@article{(Open Science Index):https://publications.waset.org/pdf/8329,
	  title     = {Persian Printed Numeral Characters Recognition Using Geometrical Central Moments and Fuzzy Min-Max Neural Network},
	  author    = {Hamid Reza Boveiri},
	  country	= {},
	  institution	= {},
	  abstract     = {In this paper, a new proposed system for Persian
printed numeral characters recognition with emphasis on
representation and recognition stages is introduced. For the first time,
in Persian optical character recognition, geometrical central moments
as character image descriptor and fuzzy min-max neural network for
Persian numeral character recognition has been used. Set of different
experiments on binary images of regular, translated, rotated and
scaled Persian numeral characters has been done and variety of
results has been presented. The best result was 99.16% correct
recognition demonstrating geometrical central moments and fuzzy
min-max neural network are adequate for Persian printed numeral
character recognition.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {4},
	  number    = {1},
	  year      = {2010},
	  pages     = {136 - 142},
	  ee        = {https://publications.waset.org/pdf/8329},
	  url   	= {https://publications.waset.org/vol/37},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 37, 2010},