• DocumentCode
    1343779
  • Title

    A thinning algorithm for Arabic characters using ART2 neural network

  • Author

    Altuwaijri, Majid M. ; Bayoumi, Magdy A.

  • Author_Institution
    King Khalid Miltary Acad., Saudi Nat. Guard, Riyadh, Saudi Arabia
  • Volume
    45
  • Issue
    2
  • fYear
    1998
  • fDate
    2/1/1998 12:00:00 AM
  • Firstpage
    260
  • Lastpage
    264
  • Abstract
    The authors propose a thinning algorithm based on clustering the image data. They employ the ART2 network which is a self-organizing neural network for the clustering of Arabic characters. The skeleton is generated by plotting the cluster centers and connecting adjacent clusters by straight lines. This algorithm produces skeletons which are superior to the outputs of the conventional algorithms. It achieves a higher data-reduction efficiency and much simpler skeletons with less noise spurs. Moreover, to make the algorithm appropriate for real-time applications, an optimization technique is developed to reduce the time complexity of the algorithm. The developed algorithm is not limited to Arabic characters, and it can also be used to skeletonize characters of other languages
  • Keywords
    ART neural nets; character recognition; computational complexity; image recognition; optimisation; real-time systems; ART2 neural network; Arabic characters; character skeletonization; data-reduction efficiency; image data clustering; optimization technique; real-time applications; self-organizing neural network; thinning algorithm; time complexity reduction; Algorithm design and analysis; Character recognition; Clustering algorithms; Heuristic algorithms; Iterative algorithms; Iterative methods; Military computing; Neural networks; Signal processing algorithms; Skeleton;
  • fLanguage
    English
  • Journal_Title
    Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7130
  • Type

    jour

  • DOI
    10.1109/82.661669
  • Filename
    661669