Evolutionary Metric-Learning-Based Recognition Algorithm for Online Isolated Persian/Arabic Characters, Reconstructed Using Inertial Pen Signals

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@Article{Sepahvand:2017:ieeeTCYB,
  author =       "Majid Sepahvand and Fardin Abdali-Mohammadi and 
                 Farhad Mardukhi",
  journal =      "IEEE Transactions on Cybernetics",
  title =        "Evolutionary Metric-Learning-Based Recognition
                 Algorithm for Online Isolated Persian/Arabic
                 Characters, Reconstructed Using Inertial Pen Signals",
  abstract =     "The development of sensors with the micro
                 electromechanical systems technology expedites the
                 emergence of new tools for human-computer interaction,
                 such as inertial pens. These pens, which are used as
                 writing tools, do not depend on a specific embedded
                 hardware, and thus, they are inexpensive. Most of the
                 available inertial pen character recognition approaches
                 use the low-level features of inertial signals. This
                 paper introduces a Persian/Arabic handwriting character
                 recognition system for inertial-sensor-equipped pens.
                 First, the motion trajectory of the inertial pen is
                 reconstructed to estimate the position signals by using
                 the theory of inertial navigation systems. The position
                 signals are then used to extract high-level geometrical
                 features. A new metric learning technique is then
                 adopted to enhance the accuracy of character
                 classification. To this end, a characteristic function
                 is calculated for each character using a genetic
                 programming algorithm. These functions form a metric
                 kernel classifying all the characters. The experimental
                 results show that the performance of the proposed
                 method is superior to that of one of the
                 state-of-the-art works in terms of recognizing
                 Persian/Arabic handwriting characters.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/TCYB.2016.2633318",
  ISSN =         "2168-2267",
  notes =        "Also known as \cite{7782360}",
}

Genetic Programming entries for Majid Sepahvand Fardin Abdali-Mohammadi Farhad Mardukhi

Citations