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• [P861] Zone Based Hybrid Feature Extraction Algorithm for Handwritten Numeral Recognition of Four Indian Scripts
  Author(s): S. V. Rajashekararadhya, Vanaja P Ranjan
  
  

  Abstract
  India is a multi-lingual and multi-script country, where eighteen official scripts are accepted and have over hundred regional languages. In this paper we propose hybrid zone based angle feature extraction system. The character centroid is computed and the image (character/numeral) is further divided in to n equal zones. Average angle from the character centroid to the pixels present in the zone is computed (one feature). Similarly zone centroid is computed (two features). Average angle from the zone centroid to the pixels present in the zone is computed (one feature). This procedure is repeated sequentially for all the zones/grids/boxes present in the numeral image. There could be some zones that are empty, and then the value of that particular zone image value in the feature vector is zero. Finally 4*n such features are extracted. Nearest neighbor and support vector machine classifiers are used for subsequent classification and recognition purpose. We obtained 97.85 %, 96.8 %, 95.1% and 95 % recognition rate for Kannada, Telugu, Tamil and Malayalam numerals respectively using support vector machine.

  
   

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