eCS: Enhanced Character Segmentation – A Structural Approach for Handwritten Kannada Scripts

  • C. Naveena
  • V. N. Manjunath Aradhya
  • S. K. Niranjan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8284)


To build an efficient OCR system, preprocessing task of segmentation process should be in accurate way. In segmentation process, character segmentation plays an important role to obtain clear isolated characters. Character segmentation in Kannada word is a crucial task due to the presence of bottom extension characters (called as Vatthus in Kannada and as extra modifiers in English) and Modifiers. Due to the presence of modifiers and few cursive form of characters the script becomes semi-cursive while writing. With this nature some of the letters are touching each other and also bottom extension characters may get touch to main characters. In this regard, an enhanced Character Segmentation (eCS) approach is proposed for an unconstrained handwritten Kannada scripts. The method is based on thinning, branch point and mixture models. The Expectation-Maximization (EM) algorithm is used to learn the mixture of Gaussians. A cluster mean points are used to estimate the direction and branch point as a reference point for segmenting characters. We experimentally evaluated the proposed method on Kannada words and shown encouraging results.


Character Segmentation Thinning Branch Points Mixture Models Kannada Script 


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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • C. Naveena
    • 1
  • V. N. Manjunath Aradhya
    • 2
  • S. K. Niranjan
    • 2
  1. 1.Dept. of CSEHKBK College of EngineeringBangaloreIndia
  2. 2.Dept. of Master of Computer ApplicationsSri Jayachamarajendra College of EngineeringMysoreIndia

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