New Experiments on Word Recognition Without Segmentation

  • Khalid Saeed
  • Marek Tabedzki
Conference paper


A new hybrid system for word recognition is discussed in this work. The system is based on a modification to the view-based approach presented in authors’ previous works. The system does not need thinning or segmentation of the analyzed word. The word is treated as a whole image. The characteristic vectors taken from both top and bottom views of the image are processed with the method of minimal eigenvalues of Töeplitz matrices. The obtained series of minimal eigenvalues are used for classification with Artificial Neural Networks. The results of the experiments on a set of common English words are presented.


Artificial Neural Network Characteristic Vector Characteristic Point Word Recognition Recognition Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Khalid Saeed
    • 1
  • Marek Tabedzki
    • 1
  1. 1.Faculty of Computer Science, Bialystok Technical UniversityWiejska 45APoland

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