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Neural network based radial basis function networks (RBFN) and subspace projection approach have been employed to recognize printed Kannada characters. RBFN’s are trained with wavelet features using K-means and subspace method is applied on normalized image. Use of structural features for disambiguating confused characters improved the recognition accuracy by 3% in case of subspace and by 1.6% using RBFN. Compared to subspace, a maximum recognition rate of 99.1% is achieved with RBFN using Haar wavelets and structural features

Added on September 23, 2014

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  • Product Type : Research Paper
  • License Type : Freeware
  • System Requirement : Not Applicable
  • Author : B. VijayKumar, A. G. Ramakrishnan
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