@article{(Open Science Index):https://publications.waset.org/pdf/13554,
	  title     = {Segmentation and Recognition of Handwritten Numeric Chains},
	  author    = {Salim Ouchtati and  Bedda Mouldi and  Abderrazak Lachouri},
	  country	= {},
	  institution	= {},
	  abstract     = {In this paper we present an off line system for the
recognition of the handwritten numeric chains. Our work is divided
in two big parts. The first part is the realization of a recognition
system of the isolated handwritten digits. In this case the study is
based mainly on the evaluation of neural network performances,
trained with the gradient back propagation algorithm. The used
parameters to form the input vector of the neural network are
extracted on the binary images of the digits by several methods: the
distribution sequence, the Barr features and the centred moments of
the different projections and profiles. The second part is the
extension of our system for the reading of the handwritten numeric
chains constituted of a variable number of digits. The vertical
projection is used to segment the numeric chain at isolated digits and
every digit (or segment) will be presented separately to the entry of
the system achieved in the first part (recognition system of the
isolated handwritten digits). The result of the recognition of the
numeric chain will be displayed at the exit of the global system.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {2},
	  number    = {12},
	  year      = {2008},
	  pages     = {4139 - 4146},
	  ee        = {https://publications.waset.org/pdf/13554},
	  url   	= {https://publications.waset.org/vol/24},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 24, 2008},
	}