Zone Based Hybrid Feature Extraction Algorithm for Handwritten Numeral Recognition of South Indian Scripts

  • S. V. Rajashekararadhya
  • P. Vanaja Ranjan
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 40)


India is a multi-lingual multi script country, where eighteen official scripts are accepted and have over hundred regional languages. In this paper we propose a zone based hybrid feature extraction algorithm scheme towards the recognition of off-line handwritten numerals of south Indian scripts. The character centroid is computed and the image (character/numeral) is further divided in to n equal zones. Average distance and Average angle from the character centroid to the pixels present in the zone are computed (two features). Similarly zone centroid is computed (two features). 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 classifier is used for subsequent classification and recognition purpose. We obtained 97.55 %, 94 %, 92.5% and 95.2 % recognition rate for Kannada, Telugu, Tamil and Malayalam numerals respectively.


Handwritten Character Recognition Feature Extraction Algorithm Nearest Neighbor Classifier Indian scripts 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • S. V. Rajashekararadhya
    • 1
  • P. Vanaja Ranjan
    • 2
  1. 1.Research ScholarIndia
  2. 2.Asst.professor Department of Electrical and Electronics Engineering, College of EngineeringAnna UniversityChennaiIndia

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