Excellence in Research and Innovation for Humanity
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@article{(International Science Index):http://waset.org/publications/274,
  title    = {An Efficient Feature Extraction Algorithm for the Recognition of Handwritten Arabic Digits},
  author    = {Ahmad T. Al-Taani},
  country   = {},
  institution={},
  abstract  = {In this paper, an efficient structural approach for
recognizing on-line handwritten digits is proposed. After reading
the digit from the user, the slope is estimated and normalized for
adjacent nodes. Based on the changing of signs of the slope values,
the primitives are identified and extracted. The names of these
primitives are represented by strings, and then a finite state
machine, which contains the grammars of the digits, is traced to
identify the digit. Finally, if there is any ambiguity, it will be
resolved. Experiments showed that this technique is flexible and
can achieve high recognition accuracy for the shapes of the digits
represented in this work.},
    journal   = {International Journal of Computer, Electrical, Automation, Control and Information Engineering},  volume    = {2},
  number    = {6},
  year      = {2008},
  pages     = {2221 - 2225},
  ee        = {http://waset.org/publications/274},
  url       = {http://waset.org/Publications?p=18},
  bibsource = {http://waset.org/Publications},
  issn      = {PISSN:2010-376X, EISSN:2010-3778},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 18, 2008},
}