@article{(Open Science Index):https://publications.waset.org/pdf/8497,
	  title     = {Study of Features for Hand-printed Recognition},
	  author    = {Satish Kumar},
	  country	= {},
	  institution	= {},
	  abstract     = {The feature extraction method(s) used to recognize
hand-printed characters play an important role in ICR applications.
In order to achieve high recognition rate for a recognition system, the
choice of a feature that suits for the given script is certainly an
important task. Even if a new feature required to be designed for a
given script, it is essential to know the recognition ability of the
existing features for that script. Devanagari script is being used in
various Indian languages besides Hindi the mother tongue of majority
of Indians. This research examines a variety of feature extraction
approaches, which have been used in various ICR/OCR applications,
in context to Devanagari hand-printed script. The study is conducted
theoretically and experimentally on more that 10 feature extraction
methods. The various feature extraction methods have been evaluated
on Devanagari hand-printed database comprising more than 25000
characters belonging to 43 alphabets. The recognition ability of the
features have been evaluated using three classifiers i.e. k-NN, MLP
and SVM.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {5},
	  number    = {12},
	  year      = {2011},
	  pages     = {1586 - 1598},
	  ee        = {https://publications.waset.org/pdf/8497},
	  url   	= {https://publications.waset.org/vol/60},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 60, 2011},
	}