DOI QR코드

DOI QR Code

Recognize Handwritten Urdu Script Using Kohenen Som Algorithm

  • Khan, Yunus ;
  • Nagar, Chetan
  • Received : 2011.12.20
  • Accepted : 2012.02.27
  • Published : 2012.02.29

Abstract

In this paper we use the Kohonen neural network based Self Organizing Map (SOM) algorithm for Urdu Character Recognition. Kohenen NN have more efficient in terms of performance as compare to other approaches. Classification is used to recognize hand written Urdu character. The number of possible unknown character is reducing by pre-classification with respect to subset of the total character set. So the proposed algorithm is attempt to group similar character. Members of pre-classified group are further analyzed using a statistical classifier for final recognition. A recognition rate of around 79.9% was achieved for the first choice and more than 98.5% for the top three choices. The result of this paper shows that the proposed Kohonen SOM algorithm yields promising output and feasible with other existing techniques.

Keywords

Pre-Classification;Neural Network;Handwritten character;SOM;Baseline;Statistical;Structural;Crux;Meticulous and Sobel edge detection

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